| C++ Neural Networks and Fuzzy Logic by Valluru B. Rao M&T Books, IDG Books Worldwide, Inc. ISBN: 1558515526 Pub Date: 06/01/95 |
Index
A
- ABAM see Adaptive Bi-directional Associative Memory
- abstract class, 138
- abstract data type, 22
- accumulation-distribution, 402, 404,
- activation, 3, 18, 89
- zero, 182
- Adaline, 81, 82, 102, 103, 112
- adaptation, 77, 120
- Adaptive Bi-directional Associative Memory, 181, 212
- Competitive, 212
- Differential
- Competitive, 212
- Hebbian, 212
- adaptive filters, 120
- adaptive linear element, 102
- adaptive models, 120
- adaptive parameters, 373
- adaptive resonance, 118
- Adaptive Resonance Theory I, 104, 107, 108, 115, 117, 243
- algorithm for calculations, 246
- equations for, 246
- F1 layer calculations, 247
- F2 layer calculations, 247
- modifying connection weights, 248
- Top-down inputs, 247
- two-thirds rule, 244, 245
- Adaptive Resonance Theory II, 248
- Adaptive Resonance Theory III, 248
- additive composition method, 506
- advancing issues, 387
- aggregation, 82, 87, 98
- Ahmadian, 513
- Aiken, 405
- algorithm, 1
- backpropagation, 7, 103, 271, 373, 375
- constructive, 121
- data clustering, 245
- encoding, 94, 96
- learning algorithm , 61, 79, 102, 118
- adaptive steepest descent, 410
- alpha, 273, 274, 330, 372, 373, 384
- alphabet classifier system, 320
- Amari, 104
- analog, 73, 74, 322
- signal, 8
- AND operation , 64
- Anderson, 105
- annealing
- process, 430
- schedule 113
- simulated annealing, 113, 114
- Anzai, 456, 472
- application, 102, 374, 511
- nature of , 74
- approximation, 109
- architecture, 7, 81, 120, 373
- Artificial Intelligence , 6, 34
- artificial neural network , 1
- ART1 see Adaptive Resonance Theory I
- ART2 see Adaptive Resonance Theory II
- ART3 see Adaptive Resonance Theory III
- artneuron class, 249
- ASCII, 305, 306, 307, 329
- graphic characters, 306
- assocpair class
- in BAM network, 186
- association, 218
- asynchronously , 1, 14
- asynchronous update, 13, 62
- attentional subsystem, 107, 243
- Augusteijn, 512
- autoassociation , 7, 8, 82,, 92, 102, 180
- autoassociative network, 7, 64, 97, 375
- average winner distance, 296
- Azoff, 410
B
- backpropagated errors, 144
- Backpropagation, 10, 103, 104, 120, 123, 302, 325, 329, 374
- algorithm, 7, 103, 271, 373, 375
- beta, 330
- calculating error, 396
- calculations, 128, 130
- changing beta while training, 337
- choosing middle layer size, 372
- convergence, 372
- momentum term, 330
- noise factor, 336
- self-supervised, 375
- simulator, 134, 173, 337, 375, 377, 396
- training and testing, 396
- training law, 333
- variations of , 373
- Baer, 516
- BAM see Bi-directional Associative Memory
- bar
- chart, 403, 404
- features, 513
- Barrons, 377, 378, 388
- base class , 25, 28, 138
- beta, 136, 337, 372, 373, 384
- bias, 16, 77, 125, 128, 378
- Bi-directional Associative Memory, 81, 92, 104, 115, 117, 179, 185, 215
- connection weight matrix, 212
- continuous, 211
- inputs, 180
- network, 104
- outputs, 180
- training, 181
- Unipolar Binary, 212
- bin, 325
- binary , 8, 15, 51, 65, 73, 74, 104
- input pattern, 51, 98
- patterns 11, 97
- string, 16, 62
- binary to bipolar mapping, 62, 63
- binding
- dynamic binding , 24, 139
- late binding , 24
- static binding, 139
- bipolar, 15, 17, 104
- mapping, 97
- string, 16, 62, 180
- bit pattern, 13
- Blending problem, 418
- block averages, 393
- bmneuron class, 186
- Boltzmann distribution, 113
- Boltzmann machine, 92, 112, 113, 118, 419, 512
- Booch, 21
- boolean logic, 50
- bottom-up
- connection weight, 248
- connections, 107, 244
- Box-Jenkins methodology, 406
- Brain-State-in-a-Box, 81, 82, 105
- breadth, 387, 389
- Buckles, 484
- buy/sell signals, 409, 410
C
- cache, 137
- Cader, 406
- CAM see Content-Addressable-Memory
- Carpenter, 92, 107, 117, 243, 269, 517
- car navigation, 374
- cartesian product, 479
- cascade-correlation, 512
- Cash Register game, 3, 65
- categorization of inputs, 261
- category, 37
- Cauchy distribution, 113
- Cauchy machine, 112, 113, 419
- cells
- complex cells, 106
- simple cells, 106
- center of area method, 504
- centroid, 507, 508
- character recognition, 305
- characters
- alphabetic, 305
- ASCII, 306, 307
- garbled, 322
- graphic, 306, 307
- handwritten, 320
- Chawla, 514
- Chiang, 513
- cin, 25, 58, 71
- clamping probabilities, 114
- Clinton, Hillary, 405
- C language, 21
- class, 22
- abstract class, 138
- base class, 25, 28, 138, 139
- derived class, 23, 25, 26, 144
- friend class, 23
- hierarchy, 27, 138, 139
- input_layer class, 138
- iostream class, 71
- network class, 53, 66
- output_layer class, 138
- parent class, 26
- classification, 322
- C layer, 106
- codebook vectors, 116
- Cohen, 212
- Collard, 405
- column vector, 97
- combinatorial problem, 422
- comparison layer, 244
- competition, 9, 94, 97
- competitive learning, 243
- compilers
- C++ compilers, 27
- compilation error messages, 27
- complement, 33, 185, 201, 202
- complex cells, 106
- composition
- max-min, 220
- compressor, 375
- Computer Science, 34
- conditional fuzzy
- mean, 491
- variance, 491
- conjugate gradient methods, 373
- conjunction operator, 505
- connections, 2, 93, 102
- bottom-up, 107
- excitatory, 272
- feedback , 82
- inhibitory , 272
- lateral, 93, 97, 107, 272, 276
- recurrent, 82, 107, 179
- top-down, 107
- connection weight matrix, 220
- connection weights, 89, 98
- conscience factor, 302
- constraints, 417
- constructor, 23, 28, 55, 66
- default constructor, 23
- Consumer Price Index, 387
- Content-Addressable-Memory, 5
- continuous
- Bi-directional Associative Memory, 211
- models, 98
- convergence, 78, 79, 96, 118, 119, 132, 323, 372, 373, 375
- cooperation, 9, 94
- correlation matrix, 9, 63
- correlation-product encoding, 220
- cost function, 124, 373
- Cottrell, 374
- counterpropagation, 106
- network, 92, 93, 302
- cout, 25, 58
- C++, 21
- classes, 138
- code, 36
- comments, 58
- compilers, 27
- implementation, 185
- crisp, 31, 73, 74
- data sets, 475
- rules, 48, 217
- values, 50
- cube, 84, 87, 89, 90
- cum_deltas, 331
- cycle, 78, 125
- learning cycle, 103
- cyclic information, 380
D
- data biasing, 378
- data hiding, 21, 22
- data clustering, 109, 245
- data completion, 102
- data compression, 102, 302
- Deboeck, 406
- Davalo, 457
- de la Maza, 410
- Decision support systems, 75
- declining issues, 387
- decompressor, 375
- decorrelation, 384
- default
- constructor, 23, 66
- destructor, 23
- defuzzification, 504, 506
- degenerate tour, 424
- degree of
- certainty, 31
- membership, 32, 477
- degrees of freedom, 383
- delete, 24, 144
- delta rule, 110-113
- derived class, 23, 25, 26, 144
- descendant, 139, 143
- DeSieno, 302
- destructor, 23, 24
- digital signal processing boards, 325
- dimensionality, 381, 382, 384
- directed graph, 65
- discount rate, 35
- discretization of a character, 98
- discrete models, 98
- discriminator, 517
- disjunction operator, 506
- display_input_char function, 308
- display_winner_weights function, 308
- distance
- Euclidean, 13
- Hamming, 13
- DJIA see Dow Jones Industrial Average
- DOF see degrees of freedom
- domains, 479, 484
- dot product, 11, 12, 51, 64, 65
- Dow Jones Industrial Average, 378, 386
- dual confirmation trading system, 408
- dynamic allocation of memory, 24
- dynamic binding, 24, 139
- dynamics
- adaptive, 74
- nonadaptive, 74
E
- EMA see exponential moving average
- encapsulate, 29
- encapsulation, 21, 22
- encode, 375
- encoding, 7, 81, 220
- algorithm, 94, 96
- correlation-product, 220
- phase, 94
- thermometer, 380
- time, 120
- energy, 422
- function, 119
- level, 113, 422
- surface, 177
- Engineering, 34
- epoch, 125
- Ercal, 514
- error signal, 103
- error surface, 113
- error tolerance, 136
- Euclidean distance, 13, 280, 296
- excitation, 94, 98, 276, 303
- excitatory connections, 244, 272
- exclusive or, 83
- exemplar, 181-183, 201
- class in BAM network, 186
- pairs, 135, 177
- patterns, 135, 177
- exemplar pattern, 16, 64
- exemplars, 64, 65, 74, 75, 115, 181
- Expert systems, 48, 75, 217
- exponential moving average, 399
- extended (database) model, 486
- extended-delta-bar-delta, 406
F
- factorial, 420
- FAM see Fuzzy Associative Memories
- Fast Fourier Transform, 374
- fault tolerance, 374
- feature detector, 328
- feature extraction, 7, 513
- Federal Reserve, 388, 388
- feedback, 4, 5, 93
- connections, 123, 179
- feed forward
- Backpropagation, 81, 92, 112, 115, 123, 384,
- network , 145, 406, 409, 511,
- architecture, 124,
- layout, 124,
- network, 10
- operation, 185
- type, 2
- field, 82
- filter, 322
- financial forecasting, 377
- fire, 3, 71, 87, 89
- first derivative, 380
- fiscal policy, 36
- fit values, 32, 217
- fit vector, 32, 217, 221
- floating point calculations, 519
- compilation for, 519
- F1 layer, 245
- calculations, 247
- Fogel, 76, 77
- forecasting, 102
- model, 378
- T-Bill yields, 405
- T-Note yields, 405
- forward, 93, 104
- Fourier transform, 380
- Frank, 515
- Freeman, 246, 248
- frequency
- component, 380
- signature, 374
- frequency spikes, 380
- friend class, 23, 66, 68
- F2 layer, 245
- calculations, 247
- Fukushima, 92, 106
- function
- constructor function, 28
- energy function, 119
- evaluation, 109
- fuzzy step function, 101
- hyperbolic tangent function, 100
- linear function, 99, 102
- logistic function, 86, 100
- Lyapunov function, 118, 119
- member function, 28, 308
- objective, 417
- overloading, 25, 139
- ramp function, 99, 101, 102
- reference function, 493
- sigmoid
- function, 99, 100, 126, 129, 133, 164, 177, 395
- logistic function, 100
- step function, 99, 101
- threshold function, 52, 95, 99, 101
- XOR function, 83-85, 87
- fuzzifier, 35, 36, 47
- program, 50
- fuzziness, 48, 50
- fuzzy adaptive system, 49
- fuzzy ARTMAP, 517
- fuzzy association, 217
- Fuzzy Associative Memories, 49, 50, 81, 92, 104, 115, 117, 217, 218, 473
- encoding, 219, 220
- Fuzzy Cognitive Map, 48, 49
- fuzzy conditional expectations, 490, 509
- fuzzy control , 497, 509
- system, 47, 48, 473
- fuzzy controller, 47
- fuzzy database, 473, 475, 509
- fuzzy expected value, 490
- fuzzy equivalence relation, 481
- fuzzy events, 488, 509
- conditional probability of, 491
- probability of , 490
- fuzzy inputs, 47, 73
- fuzzy logic, 31, 34, 50, 473
- controller, 473, 497, 509
- fuzzy matrix, 217
- fuzzy means, 488, 490, 509
- fuzzy numbers, 493, 496
- triangular, 496
- fuzzy OR method, 505
- fuzzy outputs, 47, 74
- fuzzy quantification, 488
- fuzzy queries, 483, 488
- fuzzy relations, 479, 509
- matrix representation, 479
- fuzzy rule base, 502-504
- fuzzy rules, 47, 50
- fuzzy set, 32, 50, 218, 477, 488
- complement, 218
- height, 218
- normal, 218
- operations, 32, 217
- fuzzy systems, 50, 217
- fuzzy-valued, 34
- fuzzy values, 477
- fuzzy variances, 488, 490, 509
- fzneuron class, 221
G
- Gader, 513
- gain , 107
- constant, 273
- parameter, 429, 467
- gain control, 243, 248
- unit, 244
- Gallant, 117
- Ganesh, 514
- Gaussian density function, 458, 459, 524
- generalization, 121, 320, 382
- ability, 121, 336
- generalized delta rule, 112, 176
- genetic algorithms, 75, 76, 385
- global
- minimum, 113, 177
- variable, 28
- Glover, 471
- gradient, 112, 113
- grandmother cells, 117
- gray scale, 305, 306, 322, 374
- grid, 214, 305
- Grossberg, 19, 92, 93, 107, 117, 243, 269
- Grossberg layer, 9, 19, 82, 92, 106, 302
H
- Hamming distance, 13, 201, 202
- handwriting analysis, 98
- handwriting recognition, 102
- handwritten characters, 92
- heap, 144
- Hebb, 110
- Hebbian
- conditioned learning, 302
- learning, 105, 110
- Hebbs rule, 110, 111
- Hecht-Nielsen, 93, 106, 302
- Herrick Payoff Index, 401
- heteroassociation, 7, 8, 82, 92, 102, 104, 180, 181
- heteroassociative network, 7, 97
- hidden layer, 2, 4, 75, 86, 89
- hierarchical neural network, 407
- hierarchies of classes, 27, 29
- Hinton, 114
- Hoff, 102, 112
- holographic neural network, 408
- Honig, 515
- Hopfield, 422, 427, 429
- memory, 73, 115, 117, 181
- Hopfield network, 9, 11-14, 16, 19, 51, 79, 81, 82, 93, 111, 119, 120, 181, 472
- Hotelling transform, 384
- Housing Starts, 387
- hybrid models, 75
- hyperbolic tangent function, 429
- hypercube, 218
- unit, 218
- hyperplane, 84
- hypersphere, 273
I
- image, 106, 302
- compression, 374
- processing, 98, 102
- five-way transform, 516
- recognition, 375
- resolution, 322
- implementation of functions, 67
- ineuron class, 66
- inference engine, 47
- inheritance, 21, 25, 26, 138
- multiple inheritance, 26
- inhibition, 9, 94, 98
- global, 428, 456
- lateral, 272, 276
- inhibitory connection, 272
- initialization of
- bottom-up weights, 250
- parameters, 246
- top-down weights, 250
- weights, 94
- inline, 165
- input, 98
- binary input, 98
- bipolar input, 98
- layer, 2, 10
- nature of , 73
- number of , 74
- patterns, 51, 65
- signals, 65
- space, 124
- vector, 53, 71, 272, 112
- input/output, 71
- inqreset function, 251
- instar, 93
- interactions, 94
- interconnections, 7
- interest rate, 387
- internal activation , 3
- intersection, 32, 33
- inverse mapping, 62, 182
- Investors Business Daily, 388
- iostream, 54, 71
- istream, 58
- iterative process, 78
J
- Jagota, 514
- January effect, 380
- Jurik, 381, 384, 392
K
- Karhunen-Loev transform, 384
- Katz, 377
- Kimoto, 408
- kohonen.dat file, 275, 298, 300, 317
- Kohonen, 19, 116, 117, 245, 271, 303, 456
- Kohonen feature map, 16, 271, 273, 303, 305, 323
- conscience factor, 302
- neighborhood size, 280, 299, 300
- training law, 273
- Kohonen layer, 9, 19, 82, 92, 106, 298, 302, 322
- class, 276
- Kohonen network, 275, 276, 280, 300, 303, 322
- applications of, 302,
- Kohonen output layer, 275
- Kohonen Self-Organizing Map, 115, 456, 471, 472
- Kosaka, 409,
- Kosko, 49, 50, 104, 215, 242, 506
- Kostenius, 408, 409
- Kronecker delta function 428, 524
L
- lambda, 136, 433
- late binding, 24
- lateral, 93
- lateral competition, 303
- laterally connected, 65
- lateral connections, 93, 97, 107, 272, 276
- lateral inhibition, 272, 276
- layer, 2, 81
- C layer, 106
- comparison, 244
- complex layer, 106
- F1, 244
- F2, 244
- Grossberg layer, 82, 92, 302
- hidden layer, 75, 81, 86, 89
- input layer, 2, 3, 82
- Kohonen layer, 82, 92, 302, 322
- middle layer, 329, 372
- output layer, 2, 82
- recognition, 244
- S layer, 106
- simple layer, 106
- layout, 52, 86, 124
- ART1, 244
- BAM , 180
- Brain-State-in-a-Box, 105
- FAM, 219
- Hopfield network, 11
- for TSP, 427
- LVQ, 117
- Madaline model, 103
- LBS Capital Management, 377
- learning, 4, 74, 98, 109, 110, 117, 118
- algorithm, 61, 79, 102, 118
- cycle, 103
- Hebbian, 105, 110
- one-shot, 117
- probabilistic, 113
- rate(parameter), 111, 112, 123, 125, 127, 136, 175
- supervised learning, 5, 110, 112, 117, 121
- time, 120
- unsupervised
- competitive learning, 271
- learning, 5, 110, 117, 121
- Learning Vector Quantizer, 115-117, 302
- least mean squared error, 111, 119, 123, 419
- rule, 111
- Le Cun, 375
- Lee, 512
- Levenberg-Marquardt optimization, 373
- Lewis, 377
- Lin, 512
- linear function, 99, 102
- linear possibility regression model, 493, 496, 509
- linear programming, 417
- integer, 417
- linearly separable, 83- 85
- LMS see least mean squared error rule
- local minimum, 113, 177, 325
- logic
- boolean logic, 50
- fuzzy logic, 31, 34, 50, 473
- logical operations, 31
- AND, 64
- logistic function, 86, 100
- Long-term memory, 6, 77- 79, 118, 472
- traces of, 243
- look-up
- memory, 5
- table, 106
- LTM see Long-term memory
- LVQ see Learning Vector Quantizer
- Lyapunov Function, 118, 119
M
- MACD see moving average convergence divergence
- Madaline, 102, 103
- main diagonal, 63, 480
- malignant melanoma, 514
- malloc, 24
- Mandelman, 378
- MAPE see mean absolute percentage error
- mapping, 123, 180
- binary to bipolar, 62, 63
- inverse, 62, 182
- nonlinear, 109
- real to binary, 180
- mapping surface, 109
- Markowitz, 470
- Marquez, 406
- Mason, 516
- matrix, 97, 521
- addition, 521
- correlation matrix, 9
- fuzzy, 217
- multiplication, 11
- product, 104, 522
- transpose, 11
- weight matrix, 97
- max_cycles, 326
- maximum, 33, 219
- max-min composition, 220, 221
- McClelland, 103
- McCulloch, 6
- McNeill, 508
- mean absolute percentage error, 406
- mean squared error, 111, 410
- Mears, 212, 214
- membership, 32
- functions, 50
- triangular, 499, 506
- rules, 49
- memorization, 121, 320, 336, 382, 397
- memorizing inputs, 273, 320
- memory, 98
- adaptive, 471
- fuzzy associative, 218, 221
- long-term memory, 6, 77-79, 118, 472
- recency based, 471
- short-term memory, 6, 77, 78, 79, 107, 118, 471
- Mendelsohn, 407, 408
- methods, 22, 145
- metric, 5, 103
- mexican hat function, 272, 273, 274, 276
- middle layer, 329, 372
- choosing size 372
- minimum, 33, 219
- global, 113, 177
- local, 113, 177, 325
- Minsky, 83
- model
- ART1, 245
- continuous, 98
- discrete, 98
- Perceptron model, 65, 68, 81, 83
- modulo, 423
- Mohamed, 513
- momentum, 325, 330, 337, 372, 400
- implementing, 331
- parameter, 119, 123, 134, 384
- term, 330, 375
- Morse, 514
- Moss, 514
- moving average convergence divergence, 401
- moving averages, 380, 399
- simple, 399
- weighted, 399
- multilayered, 92
- network, 106
- multilayer feed-forward neural network, 7
- multilayer networks, 123
- multiple inheritance, 26
- Munro, 374
N
- NF see noise factor
- NP-complete, 419, 427, 457
- NYSE see New York Stock Exchange
- Naim, 457
- neighborhood, 276, 303, 457
- size, 274, 280, 299, 300
- neighbors, 272
- Neocognitron, 81, 92, 106
- Nellis, 516
- NETTalk, 374
- network
- adaptive, 77
- architecture, 77, 384, 388
- autoassociative network, 97
- backpropagation network, 329
- bi-directional associative memory network, 104,, 88
- Brain-State-in-a-Box network, 105
- class, 53, 66
- heteroassociative networks, 97
- Hopfield network, 9, 11-14, 16, 19, 51, 79, 81, 82, 93, 111, 119, 120, 181, 472
- layout, 86
- modeling, 73
- multilayer network, 123
- nodes, 65
- Perceptron network, 65, 66, 68, 79
- radial basis function networks, 112, 114, 115
- RBF networks see radial basis function networks
- self-organizing , 269
- statistical trained networks, 112
- NeuFuz, 49
- neural network, 1, 2
- algorithms, 176
- artificial neural network, 1
- autoassociative, 375
- biological, 272
- counterpropagation, 302
- fault tolerance of, 374
- FAM, 218
- hierarchical, 407
- holographic, 408
- Kohonen, 271, 322
- multilayer, 123
- Perceptron, 65
- plug-in boards, 325
- self-organizing, 107, 269
- Tabu, 471
- two-layer, 92
- neural-trained fuzzy systems, 49
- neuromimes 2
- neuron, 1, 3
- input neurons, 82
- output neuron, 99
- new, 24, 144
- Newtons method, 373
- New York Stock Exchange, 387
- new highs, 389
- new lows, 389
- noise, 5, 330, 336, 337, 372, 375
- random, 375
- noise factor, 336
- noise-saturation dilemma, 79
- noise tolerance, 105
- noisy data, 320
- nonlinear function, 120
- nonlinear mapping, 109
- nonlinear scaling function, 10
- nonlinear optimization, 417, 422, 472
- nontraining mode, 135
- Normal distribution, 524
- normal fuzzy set, 218
- normalization of a vector, 272
- normalized inputs, 271, 381
- normalized weights, 280
- notation, 132
- nprm parameter, 433
- number bins, 43
- NYSE see New York Stock Exchange
O
- object, 22
- objective function, 417
- object-orientation, 21
- object-oriented programming language, 21
- Object-Oriented Analysis and Design, 21
- on-balance volume, 402
- on center, off surround, 97, 98
- one-shot learning, 117
- oneuron class, 66
- Operations Research, 34
- operator overloading, 25, 139
- optical character
- recognition, 245
- recognizer, 514
- optimization, 102, 109, 417
- nonlinear, 417, 422, 472
- stock portfolio, 470
- ordered pair, 32
- organization of layers for backpropagation program, 144
- orienting subsystem, 107, 243
- orthogonal, 11, 12, 51, 64, 98
- bit patterns, 64
- input vectors, 299
- set, 65
- ostream, 58
- output, 99
- layer, 2, 10
- nature of , 74
- number of , 74
- space, 124
- stream, 58
- outstar, 93, 106
- overfitting of data, 383
- overlap composition method, 506
- overloading, 21, 24
- function overloading, 25, 139
- operator overloading, 25, 139
- overtrained network, 329
P
- Papert, 83
- Parker, 103
- partitioning, 87, 88
- past_deltas, 331
- Patil, 406
- pattern
- association, 16
- binary pattern, 11, 97
- bit pattern, 99
- character, 17
- classification, 8, 98, 109
- completion, 105, 109
- matching, 8, 98
- recognition, 16, 34, 102, 108, 305, 322
- studies, 380
- system, 121
- spatial, 99, 214
- Pavlovian, 5
- Perceptron, 3, 4, 66, 73, 82, 87, 90, 93, 102, 112
- model, 65, 68, 81, 83
- multilayer Perceptron, 85, 88
- network, 65, 66, 68, 79
- single-layer Perceptron, 85
- permutations, 420
- Perry, 484
- perturbation , 5, 113
- phoneme, 303, 374
- phonetic typewriter, 303
- Pimmel, 513
- Pitts, 6
- pixel, 16, 322, 329, 374
- values, 214, 305
- plastic, 107
- plasticity, 78, 79
- plasticity-stability dilemma, 243
- Pletta, 515
- polymorphic function, 24, 28
- polymorphism, 21, 24, 27, 138
- Pomerleau, 374
- portfolio selection, 470, 472
- possibility distributions, 486, 487, 509
- relational model, 486, 487
- postprocess, 35
- postprocessing, 50
- filter , 50
- potlpair class
- in BAM network, 186
- preprocess, 35, 50
- preprocessing , 87, 379, 399
- data, 389
- filter, 50
- fuzzifier, 35
- Price is Right, 3, 65
- principal component analysis, 384
- private, 23, 26
- probabilities, 31, 419
- probability, 31, 43
- distributions, 113
- processing
- additive, 75
- hybrid, 75
- multiplicative, 75
- PROJECT operation, 485
- proposition, 31
- protected, 23, 26, 54, 143
- public, 23, 26, 53, 54
Q
- quadratic form, 119, 120, 418
- quadratic programming problem, 418
- quantification, 473, 475
- quantization levels, 322
- queries, 475, 476, 488
- fuzzy, 483, 488
R
- radial basis function networks, 112, 114, 115
- ramp function, 99, 101,, 102
- Ramsay, 515
- random number generator, 37
- range, 394
- normalized, 394, 395
- rate of change, 392, 400, 404
- function, 392
- indicator, 393, 394
- real-time recurrent learning algorithm, 515
- recall, 7, 81, 184, 220
- BAM , 184
- FAM, 220, 221
- recency based memory, 471
- recognition layer, 244
- recurrent, 13, 179
- recurrent connections, 82, 107, 179
- reference
- activation level, 456
- function, 493
- regression analysis, 406
- risk-adjusted return, 410
- relations, 476
- antisymmetric, 480, 481
- reflexive, 480, 481
- resemblance, 509
- similarity, 481, 509
- symmetric, 480, 481
- transitive, 480, 481
- relative strength index, 400, 404
- remainder, 423
- reset, 243, 247, 251, 262
- reset node, 244
- reset unit, 244
- resonance, 104, 107, 117, 118, 181, 215, 243, 269
- responsive exploration, 471
- Ressler, 512
- restrmax function, 251
- return type, 23
- reuse, 26
- Robotics, 34
- ROC see rate of change
- Rosenberg, 374
- Ross, 517
- row vector, 97, 104
- RSI see relative strength index
- rule
- delta, 110, 111
- generalized delta, 112
- Hebbian, 111
- Hebbs, 110
- rules
- fuzzy rules, 50
- Rumbaugh, 21
- Rummelhart, 103
S
- S&P 500 Index see Standard and Poors 500 Index
- Sathyanarayan Rao, 515
- saturate, 381
- scalar, 61
- scalar multiplier, 64
- second derivative, 380
- Sejnowski, 114, 374
- self-adaptation, 115
- self-connected, 53
- self-organization, 5, 6, 74, 115, 116
- self-organizing feature map, 116
- Self-Organizing Map, 245, 271
- self-organizing neural networks, 107, 117, 121
- self-supervised backpropagation, 375
- sensitivity analysis, 384
- separable, 84, 86, 88
- linearly separable, 83, 84
- subsets, 87
- separability, 84, 86
- separating
- line, 86
- plane, 85
- Sethuraman, 515
- set membership, 32
- Sharda, 406
- shift operator, 25
- Short Term Memory, 6, 77, 78, 79, 107, 118, 471
- traces of, 243
- Sigma Pi neural network , 75
- sigmoid
- activation function, 381, 387
- function, 77, 99, 126, 129, 133, 164, 177, 395
- squashing, 381
- signal filtering, 102
- signals
- analog, 98
- similarity, 486
- class, 481, 509
- level, 486
- relation, 481
- simple cells, 106
- simple moving average, 399
- simulated annealing, 113, 114
- simulator, 372, 396
- controls, 173
- mode, 138
- Skapura, 246, 248
- Slater, 515
- S layer, 106
- SMA see simple moving average
- SOM see Self-Organizing Map
- sonar target recognition, 374
- spatial
- pattern, 99, 214
- temporal pattern, 105,
- speech
- recognition, 303,
- synthesizer, 374,
- spike, 380
- squared error, 103
- squashing
- function, 384, 458, 459
- stable, 79, 107
- stability 78, 79, 118
- and plasticity, 77
- stability-plasticity dilemma, 79, 107,, 269
- STM see Short Term Memory
- Standard and Poors 500 Index, 377, 378
- forecasting, 386
- standard I/O routines, 519
- state energy, 118
- state machine, 48
- static binding, 139
- Steele, 514
- steepest descent, 112, 113, 177, 373
- step function, 99, 101
- stochastics, 402, 404
- Stoecker, 514
- Stonham, 516
- string
- binary, 62
- bipolar, 62
- structure, 7, 7
- subsample, 322
- subset, 221
- subsystem
- attentional, 107, 243
- orienting, 107, 243
- Sudjianto, 516
- summand, 422
- summation symbol, 422
- supervised , 109
- learning, 5, 110, 112, 115, 117, 121
- training 94, 110, 115, 121, 125
- Sweeney , 516
- symbolic approach, 6
T
- TSR see Terminate and Stay Resident
- Tabu , 471
- active, 471
- neural network, 471
- search, 471, 472
- Tank, 422, 427, 429
- target 378, 395
- outputs, 110, 115
- patterns, 105
- scaled, 395
- tau, 433
- technical analysis, 399
- temperature, 118
- Temporal Associative Memory, 92
- Terano, 496
- Terminate and Stay Resident programs, 519
- terminating value, 298
- termination criterion, 322
- test.dat file, 327, 328
- test mode, 135, 137, 138, 164, 173, 327, 396
- Thirty-year Treasury Bond Rate, 387
- Three-month Treasury Bill Rate, 387
- threshold
- function, 2, 3, 12, 17, 19, 52, 95, 99, 101, 125, 183
- value, 16, 52, 66, 77, 86, 87, 90, 101, 128, 456
- thresholding, 87, 185
- function, 133, 177, 182, 184, 214
- Thro, 508
- Tic-Tac-Toe, 76, 79
- time lag, 380
- time series forecasting, 406, 410
- time shifting, 395
- timeframe, 378
- tolerance, 119, 125, 173, 245, 318, 322, 328, 329, 372
- level, 78, 123
- value, 119
- top-down
- connection weight , 248
- connections, 107, 244
- top-down inputs, 247
- topology, 7
- Topology Preserving Maps, 116
- tour, 420
- traces, 243
- of STM, 243
- of LTM, 243
- trading
- commodities, 405,
- system, 378
- dual confirmation, 408
- training, 4, 74, 75, 98, 109, 110, 119, 181, 396
- fast, 107
- law, 272, 273, 274, 330, 333
- mode, 135, 137, 138, 164, 173, 396
- supervised, 94, 110, 115
- slow, 107
- time, 329
- unsupervised, 107, 110
- transpose
- of a matrix, 11, 179, 181, 183
- of a vector, 11, 63, 97, 181
- traveling salesperson(salesman) problem, 118, 119, 419
- hand calculation, 423
- Hopfield network solution-Hopfield, 427
- Hopfield network solution-Anzai, 456
- Kohonen network solution, 456
- triple, 217
- truth value, 31
- tsneuron class, 430
- TS see Tabu search
- TSP see traveling salesperson problem
- turning point predictor, 409
- turning points, 407
- two-layer networks, 92
- two-thirds rule, 107, 244, 245, 269
U
- Umano, 486
- Unemployment Rate, 387
- undertrained network, 329
- uniform distribution, 77
- union, 32
- Unipolar Binary Bi-directional Associative Memory, 212
- unit
- circle, 299
- hypercube, 218
- unit length, 273
- universal set, 33
- universe of discourse, 498, 499
- unsupervised , 107
- competitive learning, 271
- learning, 5, 110, 115, 117, 121
- training, 107, 110
V
- value
- fit value, 32
- threshold value, 16, 52, 66, 77, 86, 87, 90, 101, 128, 456
- variable
- external, 28
- global, 28
- vector, 17
- codebook vectors, 116
- column vector, 97, 104, 181
- fit vector, 32, 33
- heterassociated, 181
- input vector, 53, 71, 272, 112
- normalization of, 272
- potentially associated, 181
- quantization, 302
- row vector, 97, 181
- weight vector, 9, 96
- vector pairs, 181
- vertex, 88
- vertices, 88
- vigilance parameter, 107, 243, 245, 247, 262
- virtual, 24, 139
- trading, 377
- visibility, 26
- visible, 53
W
- walk-forward methodology, 408
- Wall Street Journal, 388
- Wasserman, 516
- weight matrix, 9, 17, 51, 65, 97, 181, 183
- weight sharing, 375
- weight surface, 113
- weight update, 276
- weight vector, 9, 96
- quantizing, 307
- weighted sum, 2, 3, 19, 271
- weights , 4, 181
- bottom-up, 250
- connection , 89, 98
- top-down, 250
- Werbos, 103
- Wetherell, 514
- Widrow, 102, 112
- winner indexes, 298
- winner, 98
- neuron, 323
- winner-take-all, 97, 98, 115, 116, 243, 271, 274
- World Wide Web, 388
- Wu, 515
X
- XOR function, 83-85, 87
Y
- Yan, 473, 497
- Yu, 212, 214
- Yuret, 410
Z
- zero pattern, 65
- zero-one programming problem, 471
- Zipser, 374
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