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Fukunaga K. — Introduction to Statistical Pattern Recognition
Fukunaga K. — Introduction to Statistical Pattern Recognition

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Название: Introduction to Statistical Pattern Recognition

Автор: Fukunaga K.

Аннотация:

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.


Язык: en

Рубрика: Computer science/Обработка изображений/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: second edition

Год издания: 1991

Количество страниц: 591

Добавлена в каталог: 17.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Absolute correction rule      see Correction rule
Autocorrelation function      418
Autocorrelation matrix      see Matrix
Autocorrelation mixture      see Scatter matrix mixture
Bahadur expansion      see Expansion
Basis function      287 385 417
Basis vector      401
Basis, complete set of      417
Bayes, classifier      see Classifier
Bayes, conditional cost      57
Bayes, conditional error      52
Bayes, decision rule      see Decision rule
Bayes, error      see Error
Bayes, estimate      see Successive Bayes estimation
Bayes, linear classifier      see Linear classifier
Bayes, theorem      12 52
Beta distribution      see Distribution
Bhattacharyya, bound      99
Bhattacharyya, distance      see Distance
Bhattacharyya, estimate      see Estimate
Binary input      173 290
Binary input, density function of      290
Binary input, discriminant function for      131
Binary input, orthonormality of      174 291
Binomial distribution      see Distribution
bisector      128 444 517
Block toeplitz matrix      see Matrix
Bootstrap      238
Bootstrap, bias      243
Bootstrap, error      240
Bootstrap, method      238
Bootstrap, samples      239
Bootstrap, variance      246
Branch and bound for nearest neighbor      361
Branch and bound, clustering      523
Branch and bound, feature subset selection      491
Branch and bound, feature subset selection, basic algorithm      494
Branch and bound, feature subset selection, improved algorithm      496
Burdick’s chart      63
Central limit theorem      17
Characteristic equation      26
Characteristic function      16 88
Characteristic function of likelihood ratio      88
Characteristic function of normal distribution      16 91
Chernoff bound      98
Chernoff distance      see Distance
Chi-square distribution      83 see gamma
Circular error      see Error
Class probability      see Probability
Class separability      see Separability
Classification      510
Classification supervised      51
Classification unsupervised      508
Classifier      see also Decision rule
Classifier, correlation      125
Classifier, design      7
Classifier, distance      127
Classifier, linear      see Linear classifier
Classifier, piecewise      see Piecewise classifier
Classifier, quadratic      see Quadratic classifier
Clustering      508
Clustering, algorithm      511
Clustering, criterion      510
Clustering, graph theoretic approach      539
Clustering, nearest local-mean reclassification rule      see Nearest local-mean reclassification rule
Clustering, nearest mean reclassification rule      see Nearest mean reclassification rule
Clustering, nonparametric approach      533
Clustering, normal decomposition      see Normal decomposition
Clustering, parametric aproach      510
Clustering, valley-seeking      534 542
Colored noise      128
Column correlation coefficient      164
Condensed nearest neighbor      see kNN
Configuration      510
Confusion matrix      518
Conjugate pair      see Density function
Convergence for linearly separable case      153 371
Convergence in mean-square sense      381
Convergence of nearest mean reclassification rule      see Nearest mean reclassification rule
Convergence of stochastic approximation      378
Convergence with probability 1      381
Convergence, acceleration of      388
Correction rule, absolute      369
Correction rule, fixed increment      369
Correction rule, gradient      369
Correlation      125
Correlation, classifier      15 see
Correlation, matrix      see Matrix
Cost of decision      57
Cost, conditional      57
Cost, symmetrical      58
Covariance      14
Covariance function      418
Covariance matrix      see Matrix
Coverage      255 269
Data compression      409
Data display, nonparametric      353
Data display, parametric      154
Data display, risk contour      355
Data filter      537
Data reduction, nonparametric      549
Data reduction, parametric      556
Decision rule, Bayes, for minimum error      51
Decision rule, Bayes, for minimum risk      57
Decision rule, likelihood ratio      52
Decision rule, minimax      61
Decision rule, Neyman — Pearson      59
Density function      12
Density function of binary inputs      see Binary input
Density function of coverage      269
Density function of likelihood ratio      54
Density function, a posteriori      390
Density function, a priori      390
Density function, class      12
Density function, conditional      12
Density function, conjugate pair      392
Density function, estimate of k nearest neighbor approach      see kNN
Density function, expansion of      287
Density function, exponential      56 70
Density function, gamma      23 69 573
Density function, gradient of      534
Density function, marginal      13
Density function, mixture      12
Density function, Parzen approach      see Parzen
Density function, reproducing pair      392
Design sample      see Sample
Desired output      145 147
Desired output, vector      149
Diagonal matrix      see Matrix
Diagonalization      27
Diagonalization, simultaneous      31
Dimensionality      426
Dimensionality, intrinsic      280 537
Dimensionality, local      see Dimensionality intrinsic
Directed, path      539
Directed, tree      539
Discriminant analysis      445
Discriminant analysis, nonparametric      466
Discriminant function      52
Discriminant function for binary inputs      see Binary input
Discriminant function, desired output of      see Desired output
Discriminant function, linear      see Linear classifier
Discriminant function, piecewise      see Piecewise classifier
Discriminant function, quadratic      see Quadratic classifier
dispersion      13
Distance classifier      see Classifier
Distance, between-sample      411
Distance, Bhattacharyya      99 188
Distance, Bhattacharyya, for feature extraction      455
Distance, Chernoff      98
Distance, distribution of      see Distribution
Distance, normalized      16
Distribution of distance      68
Distribution, Beta      75 270 573
Distribution, binomial      200
Distribution, function      11
Distribution, Gaussian — Wishart      393
Distribution, normal      16 573
Distribution, normal, characteristic function of      16
Distribution, normal, conditional density      48
Distribution, normal, entropy      412
Distribution, normal, generation of      30
Distribution, normal, likelihood ratio for      54
Distribution, normal, marginal density      48
Distribution, normal, probability of error for      91
Distribution, normal, test of      see Normality test
Distribution, normal, Wishart      392
Distributional test      476
Divergence      458
Double exponential waveform      284 472
Edited k nearest neighbor      see kNN
Effective dimensionality      see Dimensionality intrinsic
Eigenfuhction      418
Eigenvalues      26
Eigenvalues of autocorrelation function      418
Eigenvalues, estimation of      431
Eigenvalues, matrix      see Matrix
Eigenvalues, normalization of      410
Eigenvalues, perturbation of      426
Eigenvectors      27
Eigenvectors, estimation of      431
Eigenvectors, matrix      see Matrix
Eigenvectors, perturbation of      426
entropy      412 550
Entropy for binary inputs      416
Entropy for normal distributions      see Distribution normal
Entropy, maximization      413
Entropy, minimax      415
Entropy, minimization      416 550
Error of linear classifier      85
Error of quadratic classifier      91
Error, Bayes      53
Error, circular      287
Error, conditional      52
Error, control      351
Error, counting      197 200
Error, estimate      87 197
Error, function (normal)      63 576
Error, lower bound of      220 307
Error, mean-square      145 402
Error, pairwise      284
Error, probability of      52 85 87 197
Error, reject curve      79
Error, upper bound of      97 220 307
Estimate grouped error      356
Estimate of Bhattacharyya distance      18
Estimate of Bhattacharyya distance, bias      189 190
Estimate of Bhattacharyya distance, variance      189 190
Estimate of density function      see Density function
Estimate of density gradient      534
Estimate of error      196 301 303 344
Estimate, Bayes (successive)      see Successive Bayes estimation
Estimate, biased      21 183 187 259 272 313 326 347
Estimate, consistent      19 261 273
Estimate, k nearest neighbor density      see kNN
Estimate, maximum likelihood      see Normal decomposition
Estimate, moment      see Moment
Estimate, Parzen density      see Parzen
Estimate, sample      see Sample
Estimate, unbiased      18
Estimate, variance      183 187
Expansion by basis functions      see Basis
Expansion, Bahadur      292
Expansion, Karhunen — Loeve      403 417
Expansion, kernel of      287
Expansion, square error of      288
Expansion, Walsh      292
Expected for random process      418
Expected value      13
Expected vector      13
Factor analysis      417
Feature extraction for classification      442
Feature extraction for signal representation      400
Feature extraction, general critrion for      460
Feature extraction, sequential      480
Feature ideal      444
Feature selection      see Feature extraction
Feature, space      402
Feature, subset selection      489
Feature, subset selection, backward selection      490
Feature, subset selection, branch and bound      491 see
Feature, subset selection, stepwise search technique      490
Feature, vector      402
Fisher, classifier      see Linear classifier
Fisher, criterion      134
Fixed increment rule      see Correction rule
Fourier transform for stational process      421
Fourier transform of likelihood ratio      159
Fourier transform, orthonormality of      156
Fourier transform, quadratic classifier of      159
Gamma, density      see Density function
gamma, function      23 574 578
Gaussian pulse      282 472
Gaussian — Wishart distribution      see Distribution
Goodness-of-fit      see Chi-square
Gradient correction rule      see Correction rule
Gradient of density function      see Density function
Gradient, estimate of      see Estimate
Graph theoretic clustering      see Clustering
Grouped error estimate      see Estimate
Harmonic sequence      see Sequence
Hermite polynomial      288
Holdout method      220 310
Hughes phenomena      208
Hyperellipsoid, surface area      314 573
Hyperellipsoid, volume      260 572
Hypothesis test, composite      83
Hypothesis test, multi-      66
Hypothesis test, sequential      see Sequential (hypothesis) test
Hypothesis test, simple      51
Hypothesis test, single      67
Intrinsic dimensionality      see Dimensionality
Inverse matrix      see Matrix
K nearest neighbor (NN) - volumetric      305
K nearest neighbor (NN) - volumetric, classification      303
K nearest neighbor (NN) - volumetric, classification, likelihood ratio for      303
K nearest neighbor (NN) - volumetric, density estimation      268 575
K nearest neighbor (NN) - volumetric, density estimation, bias      272
K nearest neighbor (NN) - volumetric, density estimation, consistent      273
K nearest neighbor (NN) - volumetric, density estimation, metric      275
K nearest neighbor (NN) - volumetric, density estimation, moments      270
K nearest neighbor (NN) - volumetric, density estimation, moments, approximation of      270
K nearest neighbor (NN) - volumetric, density estimation, optimal k      273
K nearest neighbor (NN) - volumetric, density estimation, optimal k, minimum IMSE      275
K nearest neighbor (NN) - volumetric, density estimation, optimal k, minimum MSE      214
K nearest neighbor (NN) - volumetric, density estimation, unbias      273
K nearest neighbor (NN) - volumetric, density estimation, variance      273
K nearest neighbor (NN) - volumetric, distance to kNN      277
K nearest neighbor (NN) - volumetric, distance to kNN, effect of parameters      278
K nearest neighbor (NN) - volumetric, error estimation, bias      347
K nearest neighbor (NN) - volumetric, error estimation, L estimate of a covariance      351
K nearest neighbor (NN) - volumetric, error estimation, leave-one-out method      303
K nearest neighbor (NN) - volumetric, error estimation, metric      303
K nearest neighbor (NN) - volumetric, error estimation, resubstitution method      303
K nearest neighbor (NN) - volumetric, progression      552
K nearest neighbor (NN), approach - voting      305
K nearest neighbor (NN), asymptotic conditional risk and error      307
K nearest neighbor (NN), asymptotic conditional risk and error, 2NN      306
K nearest neighbor (NN), asymptotic conditional risk and error, kNN      306
K nearest neighbor (NN), asymptotic conditional risk and error, multiclass      309
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