Page 250 -
P. 250

238     5 Neural Networks

                              Eberhart  RC, Dobbins RW (1990) Systems Considerations. In: Eberhart  RC.  Dobbins RW
                                 (eds) Neural Network PC Tools. A Practical Guide. Academic Press, lnc., pp 59-77.
                              Eberhart  RC,  Dobbins  RW  (1990) Software Tools.  In:  Eberhart  RC,  Dobbins  RW  (eds)
                                 Neural Network PC Tools. A Practical Guide. Academic Press, Inc., pp 81-108.
                              Eberhart  RC,  Dobbins  RW,  Hutton  LV  (1990)  Performance  Metrics.  In:  Eberhart  RC,
                                 Dobbins RW (eds) Neural  Network PC Tools. A Practical Guide. Academic Press, Inc..
                                 pp  161-174.
                              Ehrenfeucbt A,  Haussler  D,  Kearns  M, Valiant  L (1989) A General  Lower Round on  the
                                 Number of Examples Needed for Learning. Information and Computation, 82:247-261.
                              Fausset L (1994) Fundamentals of Neural Networks. Prentice Hall Inc., New Jersey.
                              Fletcher R (2000) Practical Methods of Optimization. J. Wiley & Sons Ltd.
                              Gasser  A,  Kamel  M  (1998)  Modular  Neural  Network  Classifiers:  A Comparative  Study.
                                 Journal of Intell, and Robotic Systems, 21 : 117-129.
                              Geman  S,  Bienenstock  E,  Doursat  R  (1992)  Neural  Networks  and  the  BiaslVariance
                                 Dilemma. Neural Computation, 4: 1-58.
                              Girosi  F,  Poggio  T  (1990)  Networks  and  the  Best  Approximation  Property.  Biological
                                 Cybernetics, 63: 169-176.
                              Gunn  SR  (1997) Support  Vector  Machines  for Classification  and  Regression.  Technical
                                 Report,  Image  Speech  and  Intelligent  Systems  Research  Group,  University  of
                                 Southampton.
                              Hansen  LK, Salamon P (1990) Neural  Network  Ensembles.  IEEE Tr Patt An  Mach Intell,
                                 12:993-1001.
                              Haykin S (1999) Neural  Nctworks.  A Comprehensive Foundation. Prentice  Hall Inc., New
                                 Jersey.
                              Holland  JH (1975) Adaptation  in  Natural  and  Artificial  Systems. University  of  Michigan
                                 Press, Ann Arhor.
                              Huang GB, Babri HA (1998) Upper Bounds on the Number of  Hidden Neurons in Forward
                                 Networks  with  Arbitrary  Bounded  Nonlinear  Activation  Functions.  IEEE  Tr  Neural
                                 Networks, 9:224-228.
                              Iyer  MS, Rhinehart  RR  (1999) A Method to  Determine  the  Required  Number  of  Neural-
                                 Network Training Rcpetitions. IEEE Tr Neural Networks,  10:427-432.
                               Kearns MJ, Vazirani  UV  (1997) An  Introduction  to Computational Lcarning Theory. The
                                 MIT Press.
                               Kittler J, Hatef M, Duin RPW, Matas J (1998) On Combining Classifiers. IEEE Tr Patt An
                                 Mach Intell, 20:226-238.
                               Lippmann  RP  (1987)  An  Introduction  to  Computing  with  Neural  Networks.  lEEE Acc
                                 Speech Sig Proc Magazine, 4-22.
                               Looney CG (1997) Pattern Recognition Using Neural Networks. Oxford University Press.
                               Mirchandani G, Cao W (1 989) On Hidden Neurons for Neural Nets. IEEE Tr Circ Syst, 36:
                                 661-664.
                               Mitchell TM (1997) Machine Learning. McGraw Hill Book Co., New York.
                               Nguyen  D,  Widrow  B  (1990)  Improving  the  Learning  Speed  of  Two-Layer  Neural
                                 Networks by Choosing Initial Values of the Adaptive Weighls. Proc.  1990 IEEE Int Joint
                                 Conf Neural Networks,  3:21-26.
                               Qian N (1999) On the Momentum Term in Gradient Descent Learning Algorithms. Neural
                                 Networks, 2: 145-15 1.
                               Raudys  S  (1997)  On  Dimensionality,  Sample  Size  and  Classification  Error  of
                                 Nonparametric Linear Classification Algorithms.  IEEE Tr Patt An  Mach Intell,  19:667-
                                 671.
   245   246   247   248   249   250   251   252   253   254   255