Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

Index

Acceptance boundary, 297

Algorithm

backward, 122

condensation, 131

forward, 116

forward–backward, 123

Viterbi, 125

ARIMA, 264

ARMA, 264

Autoregressive model, 264

first order, 91, 341

second order, 92, 137

Autoregressive, moving average models, 137

Back-propagation training, 175

Baseline removal, 259

Batch processing, 166

Bayes estimation, 142

Bayes' theorem, 7, 20, 48

Bayesian classification, 16, 21

Bhattacharyya upper bound, 192

Bias, 63, 142, 332

Binary measurements, 148

Branch-and-bound, 197

Chernoff bound, 192

Chi-square test, 346

Classifier

Bayes, 8, 33

Euclidean distance, 147

feed-forward neural network, 173, 317

least squared error, 166

linear, 29, 311

linear discriminant function, 162

Mahalanobis distance, 147

maximum a posteriori (MAP), 14, 35

minimum distance, 30

minimum error rate, 24, 33

nearest neighbour, 155, 312

Parzen density-based, 150, 312

perceptron, 164

quadratic, 27, 311

support vector, 168, 316

Clustering, 226

average-link, 229

characteristics, 216

complete-link, 229

hierarchical, 228

K-means, 228

quality, 227

single-link, 229

Completely

controllable, 269

observable, 272

Computational complexity, 178

Computational issues, 253

Condensing, 159, 160

Confusion matrix, 178

Consistency checks, 292, 296, 342

Control vector, 89

Controllability matrix, 269

Cost

absolute value, 50

function, 19, 33, 50

matrix, 19

quadratic, 50

uniform, 35, 50

Covariance, 63

Covariance model (CVM) based estimator, 331

Covariance models, 327

Cross-validation, 180, 312, 332

Curve ...