Soft Computing Tools and Pattern Recognition

REFERENCES

• LA Zadeh, Fuzzy Logic, Neural Networks and Soft Computing, Communications of the ACM, vol 37, pp 77–84, 1994.
   Web of Science ®Google Scholar
• S K Pal & N R Pal, Soft Computing: Goals, Tools and Feasibility, J Inst Electron and Telecom Engrs (Spl issue on neural networks), vol 42, pp 335–347, 1996.
   Google Scholar
• R O Duda & P E Hart, Pattern Classification and Scene Analysis, John Wiley, NY, 1973.
   Google Scholar
• J T Tou & R C Gonzalez, Pattern Recognition Principles, Addison-Wesley, Reading, MA, 1974.
   Google Scholar
• A Rosenfeld & A C Kak, Digital Picture Processing, Academic Press, NY, 1982.
   Google Scholar
• R C Gonzalez & P Wintz, Digital Image Processing, Addison-Wesley, Reading, MA, 1987.
   Google Scholar
• D H Ballard & C M Brown, Computer Vision, Prentice-Hall, Englewood Cliffs, NJ, 1982.
   Google Scholar
• D Marr, Vision, W H Freeman, NY, 1982.
   Google Scholar
• LA Zadeh, Fuzzy Sets, Information and Control, vol 8, pp 338–353, 1965.
   Web of Science ®Google Scholar
• D Dubois & H Prade, Fuzzy Sets and Systems: Theory and Applications, Academic Press, NY, 1980.
   Google Scholar
• J C Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, NY, 1981.
   Google Scholar
• A Kandel, Fuzzy Techniques in Pattern Recognition, Wiley Interscience, NY, 1982.
   Google Scholar
• A Kandel, Fuzzy Mathematical Techniques with Applications, Addison-Wesley, Reading, Massachusetts, 1986.
   Google Scholar
• A Kaufmann, Fuzzy Subsets-Fundamental Theoretical Elements, Academic Press, NY, 1980.
   Google Scholar
• A Kaufmann & M Gupta, Introduction to Fuzzy Mathematics, Van Nostrand Reinhold, NY, 1985.
   Google Scholar
• S K Pal & D Dutta Majumder, Fuzzy Mathematical Approach to Pattern Recognition, Wiley (Halsted), NY, 1986.
   Google Scholar
• J C Bezdek & S K Pal, (Eds), Fuzzy Models for Pattern Recognition: Methods that Search for Structures in Data, IEEE Press, NY, 1992.
   Google Scholar
• G J Klir & T Folger, Fuzzy Sets, Uncertainty and Information, Prentice Hall, NJ, 1988.
   Google Scholar
• G J Klir & B Yuan, Fuzzy Sets and Fuzzy Logic—Theory and Applications, Prentice Hall, NY, 1995.
   Google Scholar
• L A Zadeh, K S Fu, K Tanaka & M Shimura (Eds), Fuzzy Sets and Their Applications to Cognitive and Decision Process, Academic Press, London, 1975.
   Google Scholar
• W Pedrycz, Fuzzy Sets in Pattern Recognition: Methodology and Methods, Pattern Recognition, vol 23, pp 121–146, 1990.
   Web of Science ®Google Scholar
• R R Yager & L A Zadeh (Eds), An Introduction to Fuzzy Logic Applications in Intelligent Systems, Kluwer Academic, Boston, Massachusetts, 1992.
   Google Scholar
• D E Rumelhart, J McClelland & the PDP Research Group, Parallel Distributed Processing: Explorations in the Micro-structure of Cognition, vol 1, MIT Press, Cambridge, Massachusetts, 1986.
   Google Scholar
• T Kohonen, Self-organization and Associative Memory, Springer Verlag, Berlin. 1989.
   Google Scholar
• J J Hopfield, Neurons with Graded Response have Collective Computational Properties like those of Two-state Neurons, Proc National Academy of Sciences, vol 81, pp 3088–3092, 1984.
   PubMed Web of Science ®Google Scholar
• K Fukushima, Neocognitron: A Self-organizing Multilayer Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position, Biological Cybernetics, vol 36, pp 193–202, 1980.
   PubMed Web of Science ®Google Scholar
• S Grossberg (Ed), Neural Networks and Natural Intelligence, MIT Press, Reading, MA, 1988.
   Google Scholar
• Y H Pao, Adaptive Pattern Recognition and Neural Networks, Addison Wesley, Reading, Massachusetts, 1987.
   Google Scholar
• P D Wassermann, Neural Computing: Theory and Practice, Van Nostrand Reinhold, NY, 1990.
   Google Scholar
• B Kosko, Neural Networks and Fuzzy Systems, Prentice-Hall. NJ, 1992.
   Google Scholar
• LO Chua & L Yang, Cellular Neural Network: Thoery, IEEE Trans Circuits and Systems, vol 35, pp 1257–1272, 1988.
   Google Scholar
• A Ghosh, N R Pal & S K Pal, Neural Computing: An Introduction and Some Applications, Students' Jounral Inst of Electron and Telecom Engrs (Invited Paper), vol 35, pp 105–125, 1994.
   Google Scholar
• B D Ripley, Pattern Recognition and Neural Network, Cambridge University Press, NY, 1996.
   Google Scholar
• S Haykin, Neural Networks: A Comprehensive Foundation, Macmillan College Publishing Co, NY, 1994.
   Google Scholar
• L Davis (Ed), Genetic Algorithms and Simulated Annealing, Pitman Publishing, London, 1987.
   Google Scholar
• D E Goldberg, Genetic Algorithms: Search, Optimization and Machine Learning, Addison Wesley, Reading, Massachusetts, 1989.
   Google Scholar
• Z Michalewicz, Genetic Algorithms + Data Structure = Evoluation Programs, Springer Verlag, Berlin, 1992.
   Google Scholar
• L Davis (Ed), Handbook of Genetic Algorithms, Van Nostrand Reinhold, NY, 1991.
   Google Scholar
• J H Holland, Adaptation in Neural and Artificial Systems, The University of Michigan Press, Ann Arbor, 1975.
   Google Scholar
• S K Pal & P P Wang (Eds), Genetic Algorithms for Pattern Recognition, CRC Press, Boca Raton, 1996.
   Google Scholar
• JMS Prewitt, Object Enhancement and Extraction, in Picture Processing and Psycho-Pictorics. (Eds B S Lipkin & A Rosenfeld), Academic Press, NY, 1970.
   Google Scholar
• A Rosenfeld, Fuzzy Geometry of Image Subsets, Pattern Recognition Letters, vol 2, pp 311–317, 1984.
   Web of Science ®Google Scholar
• S K Pal & R A King, On Edge Detection of X-ray Images Using Fuzzy Set, IEEE Trans Patt Anal & Mach Intell, vol 5, pp 69–77, 1983.
   PubMed Web of Science ®Google Scholar
• S K Pal, Fuzzy Sets in Image Processing and Recognition, Proc Fuzz-IEEE '92 (The 1st IEEE Int Confort Fuzzy Systems), San Diego, pp 119–126, 1992.
   Google Scholar
• S K Pal & A Ghosh, Fuzzy Geometry in Image Analysis, Fuzzy Sets and Systems, vol 48. pp 23–40, 1992.
   Web of Science ®Google Scholar
• S K Pal, Fuzzy Set Theoretic Tools for Image Analysis, in Advances in Electronics and Electron Physics, vol 88, (Eds P Hawkes & B Kazan), Academic Press, NY, pp 247–296, 1994.
   Google Scholar
• A De Luca & S Termini, A Definition of a Non Probabilistic Entropy in the Setting of Fuzzy Set Theory, Information and Control, vol 20, pp 301–312, 1972.
   Google Scholar
• S K Pal, A Note on the Quantitative Measure of Image Enhancement Through Fuzziness, IEEE Trans Patt Anal & Mach Intell, vol 4, pp 204–208, 1982.
   PubMed Web of Science ®Google Scholar
• C A Murthy, S K Pal & D Dutta Majumder, Representation of Fuzzy Operators Using Ordinary Sets, IEEE Trans Syst, Man and Cyberns, vol 17, pp 840–847, 1987.
   Web of Science ®Google Scholar
• N R Pal & S K Pal, Entropic Thresholding, Signal Processing, vol 16, pp 97–108, 1989.
   Web of Science ®Google Scholar
• N R Pal & S K Pal, Object-Background Segmentation Using New Definitions of Entropy, IEE Proceedings-E, vol 136, pp 284–295, 1989.
   Google Scholar
• N R Pal & S K Pal, Image Model, Poisson Distribution and Object Extraction, Int J Patt Recog and Artificial Intell, vol 5, pp 459–483, 1991.
   Google Scholar
• N R Pal & S K Pal, Entropy: A New Definition and its Applications, IEEE Trans Syst, Man and Cyberns, vol 21, pp 1260–1270, 1991.
   Web of Science ®Google Scholar
• B Kosko, Fuzzy Entropy and Conditioning, Information Sciences, vol 40, pp 165–174, 1986.
   Web of Science ®Google Scholar
• S K Pal & A Ghosh, Index of Area Coverage of Fuzzy Image Subsets and Object Extraction, Pattern Recognition Letters, vol 11, pp 831–841, 1990.
   Web of Science ®Google Scholar
• S K Pal & A Rosenfeld, Image Enhancement and Thresholding by Optimization of Fuzzy Compactness, Pattern Recognition Letters, vol 7, pp 77–86, 1988.
   Web of Science ®Google Scholar
• D Dubois & M C Jaulent, A Generalized Approach to Parameter Evaluation in Fuzzy Digital Pictures, Pattern Recognition Letters, vol 6, pp 251–259, 1987.
   Web of Science ®Google Scholar
• S K Pal, R A King & A A Hashim, Automatic Gray Level Thresholding Through Index of Fuzziness and Entropy, Pattern Recognition Letter, vol 1, pp 141–146, 1983.
   Web of Science ®Google Scholar
• T L Huntsberger, C L Jacobs & R L Cannon, Iterative Fuzzy Image Segmentation, Pattern Recognition, vol 18, pp 131–138, 1985.
   Web of Science ®Google Scholar
• M Trivedi & J C Bezdek, Low-level Segmentation of Aerial Images with Fuzzy Clustering, IEEE Trans Syst, Man and Cyberns, vol 16, pp 589–598, 1986.
   Web of Science ®Google Scholar
• R L Cannon, R Dave, J C Bezdek & M Trivedi, Segmentation of a Thematic Mapper Image Using the Fuzzy c- means Clustering Algorithm, IEEE Trans Geoscience and Remote Sensing, vol 24, pp 400–407, 1986.
   Web of Science ®Google Scholar
• L O Hall, A M Bensaid, L P Clarke, R P Velthuizn, M S Silbiger & J C Bezdek, A Comparison of Neural Networks and Fuzzy Clustering Techniques in Segmenting Magnetic Resonance Images of the Brain, IEEE Trans Neural Networks. vol 3, pp 672–682, 1992.
   PubMed Web of Science ®Google Scholar
• S K Pal & A Ghosh, Image Segmentation Using Fuzzy Correlation, Information Sciences, vol 62, pp 223–250, 1992.
   Web of Science ®Google Scholar
• C A Murthy & S K Pal, Fuzzy Thresholding: Mathematical Framework, Bound Functions and Weighted Moving Average Technique, Pattern Recognition Letters, vol 11, pp 197–206, 1990.
   Web of Science ®Google Scholar
• C A Murthy & S K Pal, Histogram Thresholding by Minimizing Gray Level Fuzziness, Information Sciences, vol 60, pp 107–135, 1992.
   Web of Science ®Google Scholar
• S K Pal, Fuzziness, Image Information and Uncertainty Management in Pattern Recognition (Invited Paper), J Sci Indust Research, vol 51, pp 71–98, 1992.
   Web of Science ®Google Scholar
• S K Pal & A Dasgupta, Spectral Fuzzy Sets and Soft Thresholding, Information Sciences, vol 65, pp 65–97, 1992.
   Web of Science ®Google Scholar
• N R Pal & S K Pal, A Review on Image Segmentation Techniques. Pattern Recognition, vol 26, pp 1277–1294, 1993.
   Web of Science ®Google Scholar
• X W Xie, An Information Measure for a Color Space, Fuzzy Sets and Systems, vol 36, pp 157–165, 1990.
   Web of Science ®Google Scholar
• S K Pal, Image Enhancement and a Quantitative Index Using Fuzzy Sets, Int J Syst Sci, vol 18, pp 1783–1797, 1987.
   Web of Science ®Google Scholar
• S K Pal & N R Pal, Segmentation Based on Measures of Contrast, Homogeneity, and Region Size, IEEE Trans Syst, Man and Cyberns, vol 17, pp 857–868, 1987.
   Web of Science ®Google Scholar
• M K Kundu & S K Pal, Automatic Selection of Object Enhancement Operator with Quantitative Justification Based on Fuzzy Set Theoretic Measures, Pattern Recognition Letters, vol 11, pp 811–829, 1990.
   Web of Science ®Google Scholar
• S K Pal, Fuzzy Tools for the Management of Uncertainty in Pattern Recognition, Image Analysis, Vision and Expert System, Int J Syst Sci, vol 22, pp 511–549, 1991.
   Web of Science ®Google Scholar
• N R Pal & S K Pal, Higher Order Fuzzy Entropy and Hybrid Entropy of a Set, Information Sciences, vol 61, pp 211–231. 1992.
   Web of Science ®Google Scholar
• C A Murthy & S K Pal, Bounds for Membership Function: Correlation Based Approach, Information Sciences, vol 65, pp 143–171, 1992.
   Web of Science ®Google Scholar
• N R Pal & S K Pal, Some Properties of the Exponential Entropy, Information Sciences, vol 66, pp 119–137, 1992.
   Web of Science ®Google Scholar
• K Tanaka & M Sugeno, A Study on Subjective Evaluations of Printed Color Images, Int J Approx Reason, vol 5, pp 213–222, 1991.
   Google Scholar
• S K Pal & A Rosenfeld, A Fuzzy Medial Axis Transformation Based on Fuzzy Disk, Pattern Recognition Letters, vol 12, pp 585–590. 1991.
   Web of Science ®Google Scholar
• S K Pal & L Wang, Fuzzy Medial Axis Transformation (FMAT): Practical Feasibility, Fuzzy Sets and Systems, vol 50, pp 15–34, 1992.
   Web of Science ®Google Scholar
• S K Pal, Fuzzy Skeletonization of Image, Pattern Recognition Letters, vol 10, pp 17–23, 1989.
   Web of Science ®Google Scholar
• ET Lee, Shape-oriented Chromosome Classification, IEEE Trans Syst, Man and Cyberns, vol 5, pp 629–632, 1975.
   Web of Science ®Google Scholar
• A Pathak & S K Pal, Fuzzy Grammar in Syntactic Recognition of Skeletal Maturity from X-ray, IEEE Trans Syst, Man and Cyberns, vol 16, pp 657–667, 1986.
   Web of Science ®Google Scholar
• S K Pal & A Bhattacharyya, Pattern Recognition Techniques in Analyzing the Effect of Thiourea in Brain Neurosecretory Cells, Pattern Recognition Letters, vol 11, pp 443–452, 1990.
   Web of Science ®Google Scholar
• S K Pal, Uncertainty Management in Space Station Autonomous Research: Pattern Recognition Perspective, Information Sciences, vol 72, pp 1–63, 1993.
   Web of Science ®Google Scholar
• J C Bezdek & P F Castelez, Prototype Classification and Feature Selection with Fuzzy Sets, IEEE Trans Syst, Man and Cyberns, vol 7, pp 87–92. 1977.
   Web of Science ®Google Scholar
• S K Pal & B Chakraborty, Fuzzy Set Theoretic Measures for Automatic Feature Evaluation, IEEE Trans Syst, Man and Cyberns, vol 16, pp 754–760, 1986.
   Web of Science ®Google Scholar
• S K Pal, Fuzzy Set Theoretic Measures for Automatic Feature Evalualion-II, Information Sciences, vol 64, pp 165–179. 1992.
   Web of Science ®Google Scholar
• R K De, N R Pal & S K Pal, Feature Analysis: Neural Network and Fuzzy Set Theoretic Approaches, Pattern Recognition, vol 30, pp 1579–1590, 1997.
   Web of Science ®Google Scholar
• A K Nath, S W Liu & T T Lee, On Some Properties of Linguistic Variables as Input, Fuzzy Sets and Systems, vol 17, pp 297–311, 1985.
   Web of Science ®Google Scholar
• D P Mandal, C A Murthy & S K Pal, Formulation of a Multivalued Recognition System, IEEE Trans Syst, Man and Cyberns, vol 22, pp 607–620, 1992.
   Web of Science ®Google Scholar
• DP Mandai. C A Murhty & S K Pal, Theoretical Performance of a Multivalued Recognition System, IEEE Trans Syst, Man and Cyberns, vol 24, pp 1001–1021. 1994.
   Web of Science ®Google Scholar
• S K Pal & D P Mandal, Linguistic Recognition System Based on Approximate Reasoning, Information Sciences, vol 61, pp 135–161, 1992.
   Web of Science ®Google Scholar
• M Roubens, Pattern Classification Problems and Fuzzy Sets, Fuzzy Sets and Systems, vol 1, pp 239–253, 1978.
   Google Scholar
• J M Keller, M R Gray & J A Givens, A Fuzzy k-nearest Neighbour Algorithm, IEEE Trans Syst, Man and Cyberns, vol 15, pp 580–585, 1985.
   Web of Science ®Google Scholar
• R Bellman, R Kalaba & L Zadeh, Abstraction and Pattern Classification, J Mathematical Analysis Applications, vol 13, pp 1–7, 1966.
   Web of Science ®Google Scholar
• B B Devi & V V S Sarma, A Fuzzy Approximation Scheme for Sequential Learning in Pattern Recognition, IEEE Trans Syst, Man and Cyberns, vol 16, pp 668–679, 1986.
   Web of Science ®Google Scholar
• D P Mandal, C A Murthy & S K Pal, Determining the Shape of a Pattern Class From Sampled Points in R2, Int J General Systems, vol 20, pp 307–339, 1992.
   Web of Science ®Google Scholar
• E Ruspini, A New Approach to Clustering, Information and Control, vol 15, pp 22–32, 1969.
   Google Scholar
• M Windham, Geometric Fuzzy Clustering Algorithms, Fuzzy Sets and Systems, vol 10, pp 271–279, 1983.
   Web of Science ®Google Scholar
• . E Backer & A K Jain, A Clustering Performance Measure Based on Fuzzy Set Decomposition, IEEE Trans Patt Anal & Mach Intell, vol 3, pp 66–75, 1981.
   PubMed Web of Science ®Google Scholar
• . M Roubens, Fuzzy Clustering Algorithms and their Cluster Validity, European J Operation Research, vol 10, pp 294–301, 1982.
   Web of Science ®Google Scholar
• . X L Xie & G Beni, A Validity Measure for Fuzzy Clustering, IEEE Trans Patt Anal & Mach Intell, vol 13, pp 841–847, 1991.
   Web of Science ®Google Scholar
• . R Dave, Fuzzy c-shell Clustering and Applications to Circle Detection in Digital Images, Int J General Systems, vol 16, pp 343–355, 1990.
   Web of Science ®Google Scholar
• . S K Pal & S Mitra, Fuzzy Dynamic Clustering Algorithm, Pattern Recognition Letters, vol 11, pp 525–535, 1990.
   Web of Science ®Google Scholar
• . D P Mandal, C A Murthy & S K Pal, Utility of Multiple Choices in Detecting Ill-defined Roadlike Structures, Fuzzy Sets and Systems, vol 64, pp 213–228, 1994.
   Web of Science ®Google Scholar
• . DP Mandal, C A Murthy & S K Pal, A Remote Sensing Application of a Fuzzy Classifier, Int J Uncertainty, Fuzziness and Knowledge-Based Systems, vol 2, pp 287–295, 1994.
   Google Scholar
• . S K Pal & A B Leigh, Motion Frame Analysis and Scene Abstraction: Discrimination Ability of Fuzziness Measures, Journal of Intelligent & Fuzzy Systems, vol 3, pp 247–256, 1995.
   Web of Science ®Google Scholar
• . D P Mandal, C A Murthy & S K Pal, Analysis of IRS Imagery for Detecting Man-made Objects with a Multivalued Recognition System, IEEE Trans Syst, Man and Cyberns, Part A, vol 26, pp 241–247, 1996.
   Google Scholar
• . S K Pal & S Mitra, Noisy Fingerprint Classification using Multilayered Perceptron with Fuzzy Geometrical and Textual Features, Fuzzy Sets and Systems, vol 80, pp 121–132, 1996.
   Web of Science ®Google Scholar
• . S K Pal & S N Sarbadhikari, Classification of Distorted Overlapping Fingerprints with Fuzzy Geometrical Features, Int J Knowledge-based Intelligent Engg Syst, vol 1, pp 120–137, 1997.
   Google Scholar
• . A Malaviya & L Peters, Fuzzy Feature Description of Handwriting Patterns, Pattern Recognition, vol 30, pp 1591–1609, 1997.
   Web of Science ®Google Scholar
• Special Issue on Neural Network Hardware Design, IEEE Trans Neural Networks, vol 3, 1992.
   Web of Science ®Google Scholar
• . U Ramacher & U Ruckert (Eds), VLSI Design of Neural Networks, Kluwer Academic Press, Massachusetts, 1991.
   Google Scholar
• . ME Robinson, H Yoneda & E Sanches-Sinencio, A Modular CMOS Design of a Hamming Network, IEEE Trans Neural Networks, vol 3, pp 444–456, 1992.
   PubMed Web of Science ®Google Scholar
• . H Harrer, J A Nosset & R Stelzt, An Analog Implementation of Discretetime Cellular Neural Networks, IEEE Trans Neural Networks, vol 3, pp 466–476, 1992.
   PubMed Web of Science ®Google Scholar
• . R P Lippmann, Pattern Classification using Neural Networks, IEEE Communications Magazine, pp 47–64, 1989.
   Google Scholar
• D J Burr, Experiments on Neural Net Recognition of Spoken and Written Text, IEEE Trans Acoustics, Speech, and Signal Processing, vol 36, pp 1162–1168, 1988.
   Google Scholar
• . J Lee, R C Weger, S K Sengupta & R M Welch, A Neural Network Approach to Cloud Classification, IEEE Trans Geoscience and Remote Sensing, vol 28, pp 846–855, 1990.
   Web of Science ®Google Scholar
• . Y Hirari & Y Tsukui, Position Invariant Pattern Matching by Neural Network, IEEE Trans Syst, Man and Cyberns, vol 20, pp 816–825, 1990.
   Web of Science ®Google Scholar
• T Kanaoka, R Chellapa, M Yoshitaka & S Tomita, A Higher-order Neural Network for Distortion Invariant Pattern Recognition, Pattern Recognition, vol 13, pp 837–841, 1992.
   Web of Science ®Google Scholar
• J Basak, S Chaudhury, S K Pal & D Dutta Majumder, Matching of Structural Shape Descriptions with Hopfield Net, Int J Patt Recog and Arti Intell, vol 7, pp 377–404, 1993.
   Google Scholar
• S Mitra, S K Pal & M K Kundu, Fingerprint Classification Using Fuzzy Multilayer Perceptron, Neural Computing and Applications, vol 2, pp 227–233, 1994.
   Google Scholar
• J Basak, N R Pal & S K Pal, A connetionist System for Learning and Recognition of Structures: Application to Handwritten Characters, Neural Networks, vol 8, pp 643–57, 1995.
   Web of Science ®Google Scholar
• J Basak & S K Pal, X-tron: An Incremental Connectionist Model for Category Perceptron, IEEE Trans Neural Networks, vol 6, pp 1091–1108, 1995.
   PubMed Web of Science ®Google Scholar
• J Basak & S K Pal, PsyCOP: A Psychologically Motivated Connectionist System for Object Perception, IEEE Trans Neural Networks, vol 6, pp 1337–1354, 1995.
   PubMed Web of Science ®Google Scholar
• J Basak, C A Murthy & S K Pal, A Self-organizing Network for Mixed Category Perception, Neurocomputing, vol 10, pp 341–358, 1996.
   Web of Science ®Google Scholar
• S Mitra, S N Sarbadhikari & S K Pal, An MLP-based Model for Identifying qEEG in Depression, Int J Bio-medical Computing, vol 43, pp 179–187, 1996.
   PubMedGoogle Scholar
• AK Jain, J Mao & K M Mohiuddin, Artificial Neural Networks: A Tutorial, IEEE Computer, pp 31–44, March 1996.
   Google Scholar
• GW Cottrel & P Munro, Principal Component Analysis oflmages via Back Propagation, SPIE: Visual Communication and Image Processing, vol 1001, pp 1070–1077, 1988.
   Google Scholar
• CT Chen, E C Tsao & W C Lin, Medical Image Segmentation by a Constraint Satisfaction Neural Network, IEEE Trans Nuclear Science, vol 38, pp 678–686, 1991.
   Web of Science ®Google Scholar
• SP Luttrell, Image Compression Using a Multilayer Neural Network, Pattern Recognition Letters, vol 10, pp 1–7, 1989.
   Web of Science ®Google Scholar
• B S Manjunath, T Simchony & R Chellappa, Stochastic and Deterministic Networks for Texture Segmentation, IEEE Trans Acoustics, Speech and Signal Processing, vol 38, pp 1039–1049, 1990.
   Google Scholar
• RH Silverman & A S Noetzel, Image Processing and Pattern Recognition in Ultrasonograms by Backpropagation. Neural Networks, vol 3, pp 593–603, 1990.
   Web of Science ®Google Scholar
• J Basak, B Chanda & D Dutta Majumder. On Edge and Line Linking in Graylevel Images with Connectionist Models. IEEE Trans Syst, Man und Cyberns, vol 24, pp 413–428, 1994.
   Google Scholar
• A Ghosh, N R Pal & S K Pal, Image Segmentation Using Neural Networks, Biological Cybernetics, vol 66, pp 151–158, 1991.
   Web of Science ®Google Scholar
• A Ghosh & S K Pal, Neural Network. Self-Organisation and Object Extraction, Pattern Recognition Letters, vol 11, pp 387–397, 1992.
   Google Scholar
• A Ghosh, N R Pal & S K Pal, Object Background Classification Using Hopfield Type Neural Network, Int J Patt Recog and Arti Intell, vol 6, pp 989–1008. 1992.
   Google Scholar
• A Ghosh, N R Pal & S K Pal, Self-organization for Object Extraction using Multilayer Neural Network and Fuzziness Measures, IEEE Trans Fuzzy Systems, vol 1, pp 54–68. 1993.
   Google Scholar
• A Ghosh, N R Pal & S K Pal, Modeling of Component Failure in Neural Networks for Robustness Evaluation: An Application to Object Extraction. IEEE Trans Neural Networks, vol 6, pp 648–656, 1995.
   PubMed Web of Science ®Google Scholar
• N M Nasrabadi & W Li, Object Recognition by a Hopfield Neural Network. IEEE Trans Syst, Man and Cyberns. vol 21, pp 1523–1535. 1991.
   Web of Science ®Google Scholar
• NM Nasrabadi & C Y Choo, Hopfield Network for Stereo Vision Correspondence, IEEE Trans Neural Networks. vol 3, pp 5–13, 1992.
   PubMed Web of Science ®Google Scholar
• T J Sejnowski & C R Rosenberg, Parallel Networks that Learn to Pronounce English Text, Complex Systems, vol 1, pp 145–168, 1987.
   Google Scholar
• S I Gallant, Connectionist Expert System, Communication of the Association for Computing Machinery, vol 31. pp 152–169, 1988.
   Web of Science ®Google Scholar
• L Shastri, A Connectionist Approach to Knowledge Representation and Limited Inference, Cognitive Science, vol 12, pp 331–392. 1988.
   Web of Science ®Google Scholar
• H Narazaki & L Ralescu, A Connectionist Approach for Rule-based Inference Using an Improved Relaxation, IEEE Trans Neural Networks, vol 3, pp 741–751, 1992.
   PubMed Web of Science ®Google Scholar
• S Mitra & S K Pal, Logical Operation Based Fuzzy MLP for Classification and Rule Generation, Neural Networks, vol 7, pp 353–373, 1994.
   Web of Science ®Google Scholar
• S Mitra & S K Pal, Fuzzy Self Organization, Inferencing and Rule Generation, IEEE Trans Syst, Man and Cyberns, Part A: Systems and Humans, vol 26, pp 608–620, 1996.
   Web of Science ®Google Scholar
• S Mitra & S K Pal, Fuzzy Mulit-layer Perceptron, Inferencing and Rule Generation, IEEE Trans Neural Networks, vol 6, pp 51–63, 1995.
   PubMed Web of Science ®Google Scholar
• S Mitra & S K Pal, Neuro-fuzzy Expert Systems: Relevance, Features and Methodologies, J Inst Electron and Telecom Engrs (Spl issue on neural networks), vol 42, pp 335–347, 1996.
   Google Scholar
• D H Nguyen & B Widrow, Neural Networks for Self- learning Control Systems, IEEE Trans Control Systems Magazine, vol 10, pp 18–23, 1990.
   Google Scholar
• RR Yager, Fuzzy Logic Controllers Using Neural Network. Fuzzy Sets and Systems, vol 48, pp 53–64. 1992.
   Web of Science ®Google Scholar
• H R Berenji & P Khedkar, Learning and Tuning of Fuzzy Logic Controllers through Reinforcement, IEEE Trans Neural Networks, vol 3, pp 724–740. 1992.
   PubMed Web of Science ®Google Scholar
• A F Rocha, I R Guilherme, M Theoto, A M K Miyadahira & M S Koizumi, A Neural Net for Extracting Knowledge from Natural Language Data Base, IEEE Trans Neural Networks, vol 3, pp 819–828, 1992.
   PubMed Web of Science ®Google Scholar
• J L McClelland, Putting Knowledge in its Place: A Scheme for Parallel Processing Structures on the Fly, Cognitive Science, vol 9, pp 113–146, 1985.
   Web of Science ®Google Scholar
• H Takagi, N Suzuki, T Koda & Y Kojima, Neural Networks Designed on Approximate Reasoning Architecture and Their Applications, IEEE Trans Neural Networks, vol 3, pp 752–760, 1992.
   PubMed Web of Science ®Google Scholar
• A Weibel, T Hanazawa, G Hinton, K Shikano & K J Lang, Phoneme Recognition Using Time Delay Neural Networks, IEEE Trans Acoustics, Speech and Signal Processing, vol 37. pp 328–339, 1989.
   Google Scholar
• M A Franzani, Speech Recognition with Back-propagation, Proc 9th Annual Conference of the Engineering in Medicine and Biology Society, pp 1702–1703. 1987.
   Google Scholar
• D Whitley, T Starkweather & C Bogart, Genetic Algorithms and Neural Networks: Optimizing Connections and Connectivity, Parallel Computing, vol 14, pp 347–361, 1990.
   Web of Science ®Google Scholar
• J D Schaffer, R A Caruana & L J Eshelman, Using Genetic Search to Exploit the Emergent Behavior of Neural Networks, Physica D, vol 42, pp 244–248, 1990.
   Web of Science ®Google Scholar
• S Saha & J P Christensen, Genetic Design of Sparse Feedforward Neural Networks. Information Sciences, vol 79. pp 191–200. 1994.
   Web of Science ®Google Scholar
• SA Harp & T Samad, Genetic Synthesis of Neural Network Architecture, in Handbook of Genetic Algorithms, (Ed L Davis), Van Nostrand Reinhold, NY, pp 202–221.
   Google Scholar
• V Maniezzo, Genetic Evolution of the Topology and Weight Distribution of Neural Networks, IEEE Trans Neural Networks, vol 5, pp 39–53, 1994.
   PubMed Web of Science ®Google Scholar
• S K Pal & D Bhandari, Selection of Optimal Set of Weights in a Layered Network Using Genetic Algorithms, Information Sciences, vol 80, pp 213–234, 1994.
   Web of Science ®Google Scholar
• S K Pal, S De & A Ghosh, Designing Hopfield Type Networks Using Genetic Algorithms and its Comparison with Simulated Annealing, Int J Patt Recog Art Intell, vol 11, pp 447–461, 1997.
   Web of Science ®Google Scholar
• S Forrest, (Ed), Proceedings of 5th International Conference on Genetic Algorithms, Morgan Kaufmann, San Mateo. California, 1993.
   Google Scholar
• Z Michalewicz & C Z Janikow, Genetic Algorithms for Numerical Optimization, Statistics and Computing, vol 1, pp 75–91, 1991.
   Google Scholar
• Special Issue on Genetic Algorithms, (Ed E S Gelsema), Pattern Recognition Letters, vol 16, no 8, 1995.
   Google Scholar
• BP Buckles & F E Petry (Eds), Genetic Algorithms, IEEE Computer Society Press, Los Alamitos, 1994.
   Google Scholar
• W Pedrycz (Ed), Fuzzy Evolutionary Computation, Kluwer Academic, Boston, 1997.
   Google Scholar
• D Bhandari, C A Murthy & S K Pal, Genetic Algorithm with Elitist Model and its Convergence, Int J Pat Recog & Arti Intell, vol 10, pp 731–747, 1996.
   Web of Science ®Google Scholar
• CA Murthy, D Bhandari & S K Pal, Optimal Stopping Time for Genetic Algorithm with Elitist Model, Fundamenta Informaticae, (communicated).
   Google Scholar
• M Srinivas & L M Patnaik, Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms, IEEE Trans Syst, Man, and Cybern, vol 24, pp 656–667, 1994.
   Web of Science ®Google Scholar
• S De, S K Pal & A Ghosh, Genotypic and Phenotypic Assortative Mating in Genetic Algorithm. Information Sciences, (accepted).
   Google Scholar
• L J Eshelman, Preventing Premature Convergence in the Genetic Algorithms by Preventing Incest, Proc 4th Int Conf Genetic Algorithms, San Diego, July 1991, pp 115–122.
   Google Scholar
• D Bhandari, N R Pal & S K Pal, Directed Mutation in Genetic Algorithms, Information Sciences, vol 79, pp 251–270, 1994.
   Web of Science ®Google Scholar
• S De, A Ghosh & S K Pal, Fitness Evaluation in Genetic Algorithms with Ancestors' Influence, in Genetic Algorithm for Pattern Recognition, (Eds S K Pal and P P Wang), CRC Press, Boca Raton, pp 1–23, 1996.
   Google Scholar
• S Bandyopadhyay, C A Murthy & S K Pal, Pattern Classification with Genetic Algorithms, Pattern Recognition Letters, vol 16, pp 801–808, 1995.
   Web of Science ®Google Scholar
• S Bandyopadhyay & S K Pal, Pattern Classification with Genetic Algorithms: Incorporation of Chromosome Differentiation, Pattern Recognition Letters, vol 18, pp 119–131, 1997.
   Web of Science ®Google Scholar
• S K Pal, S Bandyopadhyay & C A Murthy, Genetic Algorithms for Generation of Class Boundaries, IEEE Trans Syst, Man and Cyberns, (accepted).
   Google Scholar
• S Bandyopadhyay, S K Pal & C A Murthy, Simulated Annealing Based Pattern Classification, Information Sciences (communicated).
   Google Scholar
• CA Murthy, S Bandyopadhyay & S K Pal, Genetic Algorithm Based Pattern Classification: Relationship with Bayes Classifier, in Genetic Algorithm for Pattern Recognition, (Eds S K Pal & P P Wang), CRC Press. Boca Raton, pp 127–144, 1996.
   Google Scholar
• S Bandyopadhyay, C A Murthy & S K Pal, Pattern Classification using Genetic Algorithms: Determination of H, Pattern Recognition Letters (communicated).
   Google Scholar
• S K Pal & D Dutta Majumder, Fuzzy Sets and Decision Making Approaches in Vowel and Speaker Recognition, IEEE Trans Syst, Man and Cyberns, vol 7, pp 625–629, 1977.
   Web of Science ®Google Scholar
• S K Pal & S Mitra, Multi-layer Perceptron, Fuzzy Sets and Classification, IEEE Trans Neural Networks, vol 3, pp 683–697, 1992.
   PubMed Web of Science ®Google Scholar
• S Bandyopadhyay & S K Pal, Relation Between VGA Classifier and MLP: Determination of Network Architecture, Pattern Recognition, (comunicated).
   Google Scholar
• S Bandyopadhyay, Pattern Classification using Genetic Algorithms, PhD Thesis, Indian Statistical Institute, Calcutta, 1998.
   Google Scholar
• R Srikanth, R George, N Warsi, D Prabhu, F Petry & B Buckles, A Variable-length Genetic Algorithm for Clustering and Classification, Pattern Recognition Letters, vol 16, pp 789–800, 1995.
   Web of Science ®Google Scholar
• LI Kuncheva, Editing the k-nearest Neighbors Rule by a Genetic Algorithm, Pattern Recognition Letters, vol 16, pp 809–814, 1995.
   Web of Science ®Google Scholar
• J Piper, Genetic Algorithm for Applying Constraints in Chromosome Classification, Pattern Recognition Letters, vol 16, pp 857–864, 1995.
   Web of Science ®Google Scholar
• K Dev & C R Murthy, A Genetic Algorithm for the Knowledge Base Partitioning Problem, Pattern Recognition Letters, vol 16, pp 873–879, 1995.
   Web of Science ®Google Scholar
• M Prakash & M N Murty, A Genetic Approach for (near) Optimal Subsets of Principal Components for Discrimination, Pattern Recognition Letters, vol 16, pp 781–787, 1995.
   Web of Science ®Google Scholar
• CA Murthy & N Chowdhury, In Search of Optimal Clusters using Genetic Algorithms, Pattern Recognition Letters, vol 17, pp 825–832, 1996.
   Web of Science ®Google Scholar
• S K Pal, D Bhandari & M K Kundu, Genetic Algorithms for Optimal Image Enhancement, Pattern Recognition Letters, vol 15, pp 261–271, 1994.
   Web of Science ®Google Scholar
• S K Mitra, C A Murthy & M K Kundu, Technique for Fractal Image Compression using Genetic Algorithm, IEEE Trans Image Processing (to appear).
   Google Scholar
• S K Mitra, C A Murthy & M K Kundu, Fractal Image Magnification Technique, Proc 9th International Symposium on System-Modelting-Control, Zakopane, Poland, 1998 (accepted).
   Google Scholar
• N R Pal, S Nandi & M K Kundu, Self-Cross-over: A New Genetic Operator and its Application to Feature Selection, Int J Syst Sci, (accepted).
   Google Scholar
• S K Pal & P K Srimani, Neurocomputing: Motivation, Models and Hybridization, IEEE Computer, vol 29, pp 24–28, 1996.
   Google Scholar
• S K Pal & A Ghosh, Neuro-fuzzy Computing for Image Processing and Pattern Recognition, Int J Syst Sci, vol 27, pp 1179–1193, 1996.
   Web of Science ®Google Scholar
• J M Keller & D J Hunt, Incorporating Fuzzy Membership Functions into the Perceptron Algorithm, IEEE Trans Patt Anal & Mach Intell, vol 7, pp 693–699, 1985.
   PubMed Web of Science ®Google Scholar
• S K Pal & S Mitra, Fuzzy Versions of Kohonen's Net and MLP Based Classification: Performance Evaluation for Certain Non-convex Decision Regions, Information Sciences, vol 76, pp 297–337, 1994.
   Web of Science ®Google Scholar
• S Mitra & S K Pal, Self-Organizing Neural Network as a Fuzzy Classifier, IEEE Trans Syst, Man and Cyberns, vol 24, pp 385–399, 1994.
   Web of Science ®Google Scholar
• L O Hall, Learning on Fuzzy Data with a Back propagation Scheme, Proceedings NAFIPS, Missouri-Columbia, 1991, pp 329–332.
   Google Scholar
• B R Kammerer, Incorporating Uncertainty in Neural Networks, Int J Patt Recog and Arti Intell, vol 6, pp 179–192, 1992.
   Google Scholar
• J M Keller & H Tahani, Implementation of Conjunctive and Disjunctive Fuzzy Logic Rules with Neural Network, Int J Approx Reason, vol 6, pp 221–240, 1991.
   Google Scholar
• J M Keller, R R Yagar & H Tahani, Neural Network Implementation of Fuzzy Logic, Fuzzy Sets and Systems, vol 45, pp 1–12, 1992.
   Web of Science ®Google Scholar
• J M Keller & R Krishnapuram, Evidence Aggregation Networks for Fuzzy Logic Inference, IEEE Trans Neural Networks, vol 3, pp 761–769, 1992.
   PubMed Web of Science ®Google Scholar
• H Takagi & I Hayashi, Artificial Neural Network Driven Fuzzy Reasoning, Int J Approx Reason, vol 5, pp 191–212, 1991.
   Google Scholar
• T L Huntsberger & P Ajjimarangsee, Parallel Self-organizing Feature Maps for Unsupervised Pattern Recognition, Int J Gen Syst, vol 16, pp 357–372, 1990.
   Web of Science ®Google Scholar
• S C Newton, S Pemmaraju & S Mitra, Adaptive Fuzzy Leader Clustering of Complex Data Sets in Pattern Recognition, IEEE Trans Neural Networks, vol 3, pp 974–800, 1992.
   Google Scholar
• P K Simpson, Min-max Neural Network—Part I: Classification, IEEE Trans Neural Networks, vol 3, pp 776–786, 1992.
   PubMed Web of Science ®Google Scholar
• P K Simpson, Min-max Neural Network—Part II: Clustering, IEEE Trans Fuzzy Systems, vol 1, pp 32–45, 1993.
   Google Scholar
• ECK Tsao, J C Bezdek & N R Pal, Fuzzy Kohonen Clustering Networks, Pattern Recognition, vol 27, pp 757–764, 1994.
   Web of Science ®Google Scholar
• N R Pal, J C Bezdek & E Tsao, Generalized Clustering Networks and Kohonen's Self-organizing Scheme, IEEE Trans Neural Networks, vol 4, pp 549–558, 1993.
   PubMed Web of Science ®Google Scholar
• R Krishnapuram & J Lee, Fuzzy Connective Based Hierachical Aggregation Networks for Decision Making, Fuzzy Sets and Systems, vol 46, pp 11–27, 1992.
   Web of Science ®Google Scholar
• R Krishnapuram & J Lee, Fuzzy Set Based Hierarchical Networks for Information Fusion in Computer Vision, Neural Networks, vol 5, pp 335–350, 1992.
   Web of Science ®Google Scholar
• W Pedrycz & H C Card, Linguistic Interpretation of Self-organizing Maps, Proc 1st IEEE Int Conf Fuzz Syst, San Diego, California, pp 371–378, 1992.
   Google Scholar
• S C Lee & E T Lee, Fuzzy Neural Networks, Mathematical Biosciences, vol 23, pp 151–177, 1975.
   Google Scholar
• T Yamakawa & S Tomada, A Fuzzy Neuron and its Applications to Pattern Recognition, Proc 3rd Int Fuzzy Syst Assoc Cong, Seattle, Washington, pp 30–38, 1989.
   Google Scholar
• S K Pal, J Basak & R K De, Fuzzy Feature Evaluation Index and Connectionist Realization, Information Sciences, (accepted).
   Google Scholar
• J Basak, R K De & S K Pal, Fuzzy Feature Evaluation Index and Connectionist Relization-II: Theoretical Analysis, Information Sciences (accepted).
   Google Scholar
• MB Gorzalczay & M D McLeish, Fuzzy Neural Network Methodology Applied to Medical Diagnosis, Proc NAFIPS '92, Puerto Vallarta, Mexico, 1992, pp 266–275.
   Google Scholar
• S Mitra, R K De & S K Pal, Knowledge Based Fuzzy MLP for Classification and Rule Generation, IEEE Trans Neural Networks, vol 8, pp 1338–1350, 1997:
   PubMed Web of Science ®Google Scholar
• A Senthil Kumar, S K Basu & K L Majumder, Robust Classification of Multispectral Data Using Multiple Neural Networks and Fuzzy Integral, IEEE Trans Geoscience Remote Sensing, vol 35, pp 787–790, 1997.
   Web of Science ®Google Scholar
• S K Pal, D Bhandari, P Harish & M K Kundu, Cellular Neural Networks, Genetic Algorithms and Object Extraction, Far East Journal of Mathematical Sciences, vol 1, pp 139–155, 1993.
   Google Scholar
• S K Pal & D Bhandari, Genetic Algorithms with Fuzzy Fitness Function for Object Extraction Using Cellular Neural Networks, Fuzzy Sets and Systems, vol 65, pp 129–139, 1994.
   Web of Science ®Google Scholar
• M Sarkar & B Yegnanarayana, Feedforward Neural Networks Configuration Using Evolutionary Programming, Proc IEEE Int Conf Neural Networks, Houston, TX, 1997, pp 438–443.
   Google Scholar
• M Sarkar & B Yegnanarayana, An Evolutionary Pro- gramming-based Probabilistic Neural Network Construction Technique, Proc IEEE Int Conf Neural Networks, Houston. TX. 1997, pp 456–461.
   Google Scholar
• N Kasabov & M Watts, Genetic Algorithms for Structural Optimization, Dynamic Adaptation and Automated Design of Fuzzy Neural Networks, Proc IEEE Int Conf Neural Networks, Houston, TX, 1997, pp 2546–2549.
   Google Scholar
• Z Pawlak, Rough Sets, Theoretic Aspects of Reasoning about Data, Kluwer Academic. Dordrecht, 1991.
   Google Scholar
• M Banerjee, S Mitra & S K Pal, Rough Fuzzy MLP: Knowledge Encoding and Classification, IEEE Trans Neural Networks, (revised and communicated).
   Google Scholar
• M Banerjee, S Mitra & S K Pal, Knowledge-Based Fuzzy MLP with Rough Sets, Proc Int Conf Neural Networks, Houston, TX, 1997, pp 499–504.
   Google Scholar
• M Banerjee & S K Pal, Roughness of a Fuzzy Set, Information Sciences, vol 93, pp 235–246, 1996.
   Web of Science ®Google Scholar
• M Sarkar & B Yegnanarayana, Rough-fuzzy Set Theoretic Approach to Evaluate the Importance of Input Features in Classification, Proc IEEE Int Conf Neural Networks, Houston, TX, 1997, pp 1590–1595.
   Google Scholar
• S K Pal & A Skowron (Eds), Fuzzy Sets, Rough Sets and Decision Making Processes, Springer Verlag, Singapore (to appear).
   Google Scholar
• Special Issue on Neural Networks: Theory and Application, (Eds S K Pal & P K Srimani), IEEE Computer, vol 29, no 3, 1996.
   Google Scholar
• Special Issue on Neural Networks, (Ed S K Pal), J Inst Electron Telecom Engrs, vol 42, no 3 & 4, 1996.
   Google Scholar
• Special Issue on Fuzzy Systems, (Ed J C Bezdek), IEEE Trans Neural Networks, vol 3, no 5, 1992.
   Google Scholar
• Special Issue on Soft Computing, (Ed S K Pal), Fundamenta Informaticae (to appear).
   Google Scholar