Neural Networks A Comprehensive Foundation

 ABBREVIATIONS

AI                artificial intelligence

APEX            adaptive principal components extraction

AR                autoregressivve

BBTT            back propagation through time

BM              Boltzmann machine

BP                back propagation

bS                bits per second

BOSS            bounded, one-sided saturation

BSB            Blind source (signal) separation

CART         classification and regression tree

cmm            correlation matrix memory

CV             cross-validationi

DEKF        decoupled extended Kalman filter

DFA        deterministic finite-state automata

DSP        digital signal processor

EKF         extended Kalman filter

EM        expectaion-maximization

FIR           finite-duration impulse response

FM            frequency-modulation(signal)

GEKF        global extended Kalman filter

GCV        generalized cross-validation

GHA        generalized Hebbian algorithm

GSLC        generalized sidelobe canceler

HME        hierarachicl mixture of experts

HMM       hidden Markov model

Hz            hertz

ICA        independent componects analysis

Infomax        maximum mutual information

KR            kernel regression

LMS            least-mean-squre

LR                likelihood ratio

LTP            long-term potentiation

LTD            long-term depression

LR            likelihood ration

LVO        learning vector quantization

MCA       minor components analysis

MDL        minimum description length

ME           mixture of experts

MFT            mean-field theory

MIMO        multiple input-multiple output

ML            maximum likelihood

MLP            multilayer perceptron

MRAC         model reference adaptive control

NARMA     nonlinear autoregressive moving average

NARX        nonlinear autoregressive with exogenous inputs

NDP         neuron-dynamic programming

NW           Nadaraya-Watson (estimator)

NWKR        Nadaraya-Watson kernal regression

OBD            optimal brain damage

OBS            optimal brain surgeon

OCR            optical character recognition

ODE            ordinary differential equation

PAC            probably approximately correct

PCA            principal components analysis

pdf            probability density function

pmf            probability mass function

RBF            radial basis function

RMLP         recurrent multialyer perceptron

RTRL            real-time recurrent learning

SIMO         single input-multiple output

SISO            single input-single output

SNR            signal-to-noise ratio

SOM            self-organizing map

SRN            simple recurrent network(also referred to as Elman's recurrent network)

SVD            singular vale decomposition

SVM            support vector machine

TDNN        time-delay neural network

TLFN        time lagged feedforward  network

VC         Vapnik-Chervononkis(dimension)

VLSI        very-large-scale integration

XOR        exclusive OR

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