ADALINE network decision boundary decision boundary Adaption custom function function parameters Adaptive filter example noise cancellation example prediction application prediction example training Adaptive linear networks Adaptive linear networks Amplitude detection Applications adaptive filtering aerospace automotive banking defense electronics entertainment financial insurance manufacturing medical medical oil and gas exploration robotics speech telecommunications transportation Architecture bias connection bias connection input connection input connection input delays layer connection layer connection layer delays number of inputs number of inputs number of layers number of layers number of outputs number of outputs number of targets number of targets output connection output connection target connection target connection Backpropagation Backpropagation algorithm example Backtracking search Batch training Batch training Batch training dynamic networks static networks Bayesian framework benchmark benchmark BFGS quasi-Newton algorithm Bias connection definition initialization function learning learning function learning parameters subobject subobject value value Box distance Brent's search Cell array derivatives errors initial layer delay states input P input vectors inputs and targets inputs property layer targets layers property matrix of concurrent vectors matrix of sequential vectors sequence of outputs sequential inputs tap delayed inputs weight matrices and bias vectors Charalambous' search Classification input vectors linear regions Code mathematical equivalents perceptron network writing Competitive layer Competitive neural network example Competitive transfer function Competitive transfer function Competitive transfer function Concurrent inputs Concurrent inputs Conjugate gradient algorithm Fletcher-Reeves update Polak-Ribiere update Powell-Beale restarts scaled Continuous stirred tank reactor Control control design electromagnet electromagnet feedback linearization feedback linearization model predictive control model predictive control model predictive control model predictive control model predictive control model predictive control model reference control model reference control model reference control model reference control model reference control model reference control NARMA-L2 NARMA-L2 NARMA-L2 NARMA-L2 NARMA-L2 NARMA-L2 plant plant plant robot arm time horizon training data CSTR Custom neural network Dead neurons Decision boundary Decision boundary definition Demonstrations appelm1 applin3 definition demohop1 demohop2 demorb4 nnd10lc nnd11gn nnd12cg nnd12m nnd12mo nnd12sd1 nnd12sd1 nnd12vl Distance Distance box custom function Euclidean link Manhattan tuning phase Dynamic network Dynamic network Dynamic networks training training Early stopping Electromagnet Electromagnet Elman network recurrent connection Euclidean distance Export networks networks training data Feedback linearization Feedback linearization Feedforward network Finite impulse response filter Finite impulse response filter Fletcher-Reeves update Generalization regularization Generalized regression network Golden section search Gradient descent algorithm Gradient descent algorithm batch with momentum with momentum Graphical User Interface Gridtop topology Hagan, Martin Hagan, Martin Hard limit transfer function Hard limit transfer function Hard limit transfer function Heuristic techniques Hidden layer definition Home neuron Hopfield network architecture design equilibrium point solution trajectories stable equilibrium point target equilibrium points Horizon Hybrid bisection-cubic search Import networks networks training data training data Incremental training Initial step size function Initialization additional functions custom function definition function parameters parameters Input concurrent connection number range size subobject subobject subobject Input vector classification dimension reduction distance outlier topology Input weights definition Inputs concurrent sequential sequential Installation guide Jacobian matrix Kohonen learning rule Lambda parameter Layer connection dimensions distance function distances initialization function net input function number positions size subobject topology function transfer function Layer weights definition Learning rate adaptive maximum stable optimal ordering phase too large tuning phase Learning rules custom Hebb Hebb with decay instar Kohonen outstar supervised learning unsupervised learning Widrow-Hoff Widrow-Hoff Widrow-Hoff Widrow-Hoff Widrow-Hoff Widrow-Hoff Learning vector quantization creation learning rule learning rule LVQ network subclasses target classes union of two sub-classes Least mean square error Least mean square error Levenberg-Marquardt algorithm reduced memory Line search function backtracking search Brent's search Charalambous' search Golden section search hybrid bisection-cubic search Linear networks design Linear transfer function Linear transfer function Linear transfer function Linear transfer function Linear transfer function Linearly dependent vectors Link distance Log-sigmoid transfer function Log-sigmoid transfer function Log-sigmoid transfer function MADALINE Magnet Magnet Manhattan distance Maximum performance increase Maximum step size Mean square error function least least Memory reduction Model predictive control Model predictive control Model predictive control Model predictive control Model predictive control Model predictive control Model reference control Model reference control Model reference control Model reference control Model reference control Model reference control Momentum constant Mu parameter NARMA-L2 NARMA-L2 NARMA-L2 NARMA-L2 NARMA-L2 NARMA-L2 Neighborhood Net input function custom Network definition dynamic dynamic static Network Function Network layer competitive definition Network/Data Manager window Neural network adaptive linear adaptive linear competitive custom definition feedforward generalized regression multiple layer multiple layer multiple layer one layer one layer one layer one layer one layer probabilistic radial basis self organizing self-organizing feature map Neural Network Design Instructor's Manual Overheads Neuron dead (not allocated) definition home Newton's method NN predictive control NN predictive control NN predictive control NN predictive control NN predictive control NN predictive control Normalization inputs and targets mean and standard deviation Notation abbreviated abbreviated layer transfer function symbols transfer function symbols Numerical optimization One step secant algorithm Ordering phase learning rate Outlier input vector Output connection number size subobject subobject Output layer definition linear Overdetermined systems Overfitting Pass definition pattern recognition Perceptron learning rule Perceptron learning rule normalized Perceptron network code creation limitations Performance function custom modified parameters Plant Plant Plant Plant identification Plant identification Plant identification Plant identification Polak-Ribiere update Postprocessing Post-training analysis Powell-Beale restarts Predictive control Predictive control Predictive control Predictive control Predictive control Predictive control Preprocessing Principal component analysis Probabilistic neural network design Quasi-Newton algorithm BFGS Radial basis design efficient network function network network design Radial basis transfer function Recurrent connection Recurrent networks Regularization automated Resilient backpropagation Robot arm Self-organizing feature map (SOFM) network neighborhood one-dimensional example two-dimensional example Self-organizing networks Sequential inputs Sequential inputs S-function Sigma parameter Simulation definition SIMULINK generating networks NNT block set NNT block set Spread constant Squashing functions Static network Static networks batch training training Subobject bias bias bias input input input input layer layer output output output target target target weight weight weight weight weight Supervised learning target output training set System identification System identification System identification System identification System identification System identification Tan-sigmoid transfer function Tapped delay line Tapped delay line Target connection number size subobject subobject Target output Time horizon Topologies gridtop Topologies for SOFM neuron locations Topology custom function Training batch batch competitive networks custom function definition definition efficient faster function incremental ordering phase parameters post-training analysis self organizing feature map styles tuning phase Training data Training set Training styles Training with noise Transfer function competitive competitive competitive custom definition derivatives hard limit hard limit linear linear linear log-sigmoid log-sigmoid log-sigmoid radial basis saturating linear soft maximum tan-sigmoid triangular basis Transformation matrix Tuning phase learning rate Tuning phase neighborhood distance Underdetermined systems Unsupervised learning Variable learning rate algorithm Vectors linearly dependent Weight definition delays delays initialization function initialization function learning learning learning function learning function learning parameters learning parameters size size subobject subobject subobject value value value weight function weight function Weight function custom Weight matrix definition Widrow-Hoff learning rule Widrow-Hoff learning rule Widrow-Hoff learning rule Widrow-Hoff learning rule Widrow-Hoff learning rule Widrow-Hoff learning rule Workspace (command line)