Gupta M.M., Jin L., Homma N. — Static and dynamic neural networks :: Электронная библиотека попечительского совета мехмата МГУ

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Gupta M.M., Jin L., Homma N. — Static and dynamic neural networks

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Название: Static and dynamic neural networks

Авторы: Gupta M.M., Jin L., Homma N.

Аннотация:

Provides comprehensive treatment of the theory of both static and dynamic neural networks.
* Theoretical concepts are illustrated by reference to practical examples Includes end-of-chapter exercises and end-of-chapter exercises.

Язык:

Рубрика: Computer science/Генетика, нейронные сети/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2003

Количество страниц: 722

Добавлена в каталог: 17.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

norm      172
norm      172 257
$\alpha$ -LMS algorithm      71
$\alpha$ -perceptron learning rule      66
$\mu$ -LMS      77
Absolute stability      445
Action potential      24 39 317
Activation function      80 301 470 511
Activation function, linear      451
Activation function, nonlinear      451
Activation function, synapse-dependent nonlinear      448
Activation gain      82 470
active state      511
ADALINE      70
Adaptation      4 12 63 94 431 652
Adaptive algorithm      64
Adaptive filter      398
Adaptive weight learning rule      113
Additive and shunting network      305
Adjoint equation      401
Affine coordinate transformation      315
Algebraic closure      240 257
Algorithm      64
Algorithm, $\alpha$ -LMS      71
Algorithm, $\mu$ -LMS      77
Algorithm, adaptive      64
Algorithm, backpropagation      83 106 118 129
Algorithm, BP      83
Algorithm, modified relaxation      69
Algorithm, momentum      144
Algorithm-based computing      10
AND operation      45
Associating learning rule      623
Associative memory      394—395 436—437 516 580
Associativity      647
Asymptotic stability      333
Asymptotically stable      474—475
Asymptotically stable in large      473
Asymptotically stable, equilibrium point      311 357
Asymptotically stable, globally      473
Asymptotically stable, locally      476
Asynchronous mode      513
Asynchronous operating mode      561
Asynchronous updating mode      594
Attraction basin      396
Attractive radius      606
Attractive region      606
Attractor      514
Autoassociative memory      398
Axon      24 28 39 581
Backpropagation      83 106 118 140 172
Backpropagation, algorithm      83 129
Backpropagation, learning      172
Backpropagation, through time      411
Basin of attraction      348
BFGS method      199
Bias      301
Bifurcation      334
Binary logic      14 45
Block sequential mode      513
Block sequential operating mode      561
Boolean function      511
Boundary condition      647
Bounded measurable function      257
bp      83 106 118 172
Brain      4 8 10
Brouwer’s fixed-point theorem      332 473
Broyden — Fletcher — Goldfarb — Shannon method      199
CAM      348 359
Canonical form      211
Carbon-based cognitive faculty      10
Carbon-based computer      4
Cartesian product      275 638
Central nervous system      8 22
CG      200
CGL      200
Chain rule      89
Chaotic attractor      396
Classification      226
Closed set      255
Closure      255
Clustering algorithm      242
CNS      8 22
Cognition      4 634
Cognitive computing machine      5
Cognitive information      7
Commutativity      647
Compact      255
Complement      637
Complexity measure      179
Complexity regularization      179
Computational complexity      246
Computational energy function      357
Conjugate gradient method      200
Conjugate gradient method with line search      200
Conjugate gradient method, scaled      200
Content-addressable memory      348 359 580 598
Continuity      383
Continuous-time      346
Continuous-time, dynamic neural network      346 396 421 436
Continuous-time, dynamic neural unit      399
Continuous-time, mapper      398
Continuous-time, mapper, recurrent neural network      380
Contraction mapping theorem      489
Convergent K-means clustering algorithm      244
Correlation coefficient      610
Correlation matrix      75
Cortex      39
Cosig function      263
Cosine squashing function      263
Cost function      113
Critical point      365
Cross-layer connection      346
CT-DNN      421 470
CT-DNU      399
Cubic splines radial basis function      229
Cycle length      514
Davidson — Fletcher — Powell method      199
DBP      395
De Morgan’s theorem      648
Dead zone      68
Deadbeat response      212
Decaying-exponential network      292
Decomposed extended Kalman filter      205 431
Defuzzifier      641 643
DEKF      205 431
Dendrite      24 27 39
Dense set      255
DFP method      199
Diagonal Lyapunov equation      483
Diagonal Lyapunov function      483
Diagonal stability      482
DIC      211
Diffeomorphism      388
Dirac’s delta function      582
Direct inverse control      211
Discrete-time      347
Discrete-time, binary neural network      510
Discrete-time, dynamic neural network      470
Discrete-time, dynamic neural structure      347
Discrete-time, dynamic neural unit      404
Dissipative property      394
Dissipative system      347
DNN      351 395 436
DNN-S      374
DNU      18 298 395
DT-DNU      404
Dynamic backpropagation      395 403
Dynamic memory      624
Dynamic neural network      18 298 351 395 436 470

Dynamic neural network with saturation      374
Dynamic neural network, continuous-time      346 436
Dynamic neural network, discrete-time      470
Dynamic neural network, Hopfield      436
Dynamic neural unit      18 298 338 395
Effective Hamming distance      591
Effective rise time      26
Eigenvalue      366 439
EKF      202 204
Energy function      357 475 519 584
Energy function, computational      357
Energy function, method      475
Equilibrium memory      338
Equilibrium point      311 331 384 394 436 473 512 584
Equilibrium point, globally exponentially stable      334
Equilibrium point, learning      394
Equilibrium point, saddle      476
Equilibrium point, stable      519
Equilibrium point, unstable      334
Error backpropagation      431
Error measure index      139
Error partial derivative      138
Euclidean distance      242
Euclidean norm      225 473 622
Euclidean space      588
Evolutionary theory      316
Excitatory operation      317
Excitatory-inhibitory neural model      317
Exponential stability      436 452
Extended Kalman filter      202 204
Fault-tolerant system      14
FBFN      671
FBP      667 669
Feedback binary associative memory      19 580
Feedforward neural network      18 254
Finite impulse response      346
FIR      346
Firing state      511
First-order pruning      183
Fixed point      473
Fixed-increment perceptron      69
Fletcher Reeves formulation      201
FMF      639
FN      645
FNN      634 655
Fourier series      258
Frequency modulation      327
Function      48
Function, activation      80
Function, hard-limiting      82
Function, linearly separable      54
Function, signum      82
Function, step      48
Function, threshold      54
Functional approximation      18 226 254
Fundamental memory      593
Fuzzifier      641
Fuzzy      8 634
Fuzzy, addition      645
Fuzzy, backpropagation      667 669
Fuzzy, basis function      678
Fuzzy, basis function network      671
Fuzzy, concept      634
Fuzzy, IF-THEN rule      634
Fuzzy, inference engine      641 643
Fuzzy, judgment      634
Fuzzy, logic      8 14 634
Fuzzy, logic operation      646
Fuzzy, membership function      639
Fuzzy, multiplication      645
Fuzzy, neural network      15 19 634 655
Fuzzy, neuron      635 645
Fuzzy, reasoning      634
Fuzzy, rule base      641—642
Fuzzy, set      636
Fuzzy, system      641
Gain      470
Gating term      183
Gaussian density function      224 235
Gaussian neural network      235
Gaussian radial basis function      224 229 291
Gaussian radial basis function, neural network      235 674
Gaussian radial membership function      673
Generalized delta rule      113 118 172
Generalized inverse      234
Generalized inverse method      245
Generalized learning rule      580 620
Gerschgorin’s theorem      441 483
Global asymptotic stability      436 444
Global exponential stability      461
Global Lyapunov function      475
Global minimum      162 369
Global stability theorem of Lyapunov      475
Globally asymptotically stable      473
Globally exponentially stable      334 474
Gradient descent method      140 245
Gradient steepest-descent method      79
Gradient-like system      365
Gram-Schmidt orthogonalization      629
GRBFNN      674
GRMF      673
Gronwall’s inequality      490
Grossberg neuron model      317
Habituation      36—37
Hamming distance      591
Hard-limiting quantizer      517
Hebbian learning rule      580
Hebb’s rule      532
hessian      191
Hessian matrix      189
Hestenes — Stiefel formulation      201
HFNN      662
Hidden layer      130
Higher-order neural network      280
Higher-order neural unit      280
Higher-order optimization      198
Homeomorphism      277
HONN      280
HONU      280
Hopfield neural network      351 479 580
Hopfield neuron model      317
Human cognition      4
Human intelligence      4
Human thinking      634
Humanlike attribute      4
Humanlike function      4
Hybrid fuzzy neural network      662 666
Hyperbolic tangent function      259
IC      45
Identity function      256
IIC      213
IIR      346
inclusion      637
Indirect inverse control      213
Infimum      255
Infinite impulse response      346
Information capacity      580
Information retrieval      580 597
Inhibitory operation      317
Input layer      130
Integrated circuit      45
Intelligence      4
Intelligent system      7
Interlayer connection      346
Internal state      301
Interpolation condition      228
Interpolation problem      224 227
Intersection      637
Intralayer connection      346
Inverse multiquadratic radial basis function      229

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