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Pal S.K., Pal A. (eds.) — Pattern Recognition: From Classical to Modern Approaches
Pal S.K., Pal A. (eds.) — Pattern Recognition: From Classical to Modern Approaches

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Название: Pattern Recognition: From Classical to Modern Approaches

Авторы: Pal S.K., Pal A. (eds.)

Аннотация:

Presents recent developments in the classical and modern hybrid methodologies currently being applied in pattern recognition. The 21 chapters deal with decision theoretic classification using the statistical approach, neural networks, the fuzzy set approach, the use of genetic algorithms, and soft computing. Topics include Bayesian approaches for unsupervised classification, networks of spiking neurons in data mining, adaptive segmentation techniques for hyperspectral imagery, and writing speed and writing sequence invariant on-line handwriting recognition.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2001

Количество страниц: 612

Добавлена в каталог: 23.03.2006

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
$\alpha$-cut      439
$\epsilon$-optimal learning algorithm      77
$\epsilon$-optimal stopping time      346
$\lambda$-fuzzy measure      439 440
1-step look-ahead      177
2-step look-ahead      177
A posteriori probability      6 510
a priori probability      6
Abstraction      11
Activation function      302
Active contours      583 585
Adaptation cycles      304
Adaptive resampling      428
Adaptive segmentation      506
Admissible grammar      205
Aggregation      436
Aggregation connective      438
Ambiguous data      312 315 324
AND neuron      232 233
ANNs      13 474
Anti-formants      535
Artificial Neural Networks      13 474 see
Asymptotic error rate      34
Asymptotic error rate, definition      35
Asymptotic error rate, logistic regression      34
Asymptotic relative efficiency      34 35
Asymptotic relative efficiency, definition      35
Asymptotic relative efficiency, logistic regression      37
Asymptotic relative efficiency, logistic regression of intercept      37 38
Asymptotic relative efficiency, logistic regression of slope      37 38
Asymptotic relative efficiency, logistic regression, formula for      37
Autoassociative neural networks (AANNs)      547
Automata, common payoff game of      92
Automata, network of      98
Automata, team of      92
Automatic target recognition      506
Auxiliary node      481
Average reward      77
Backpropagation of error      14 98 303 550
BADD defuzzification      438
Bagging      428
Bayes classification rule      26 31 34
Bayes classifier      5 6 71 510
Bayes error rate      32—34
Bayes factor      130
Bayes theorem      71 148 155 281 510
Bayesian image analysis      148
Bayesian model      125
Biometric pattern recognition      580 581
Bird contamination      305
Bird detection      324
Bird removal      307
Bird removal system      323
Bird visualization      324
Bird-contaminated spectra      319
Bookstein coordinates      151
Boosting      428
Brownian motion      101
Busyness index      262
Canonical regular grammar      204
Case-based reasoning      17
Cepstral coefficients      544
Cepstral coefficients, LP      544
Cepstral coefficients, mel-scale      544 550
Character recognition      559
Chi-square statistic      170 172
child nodes      171
Choquet integral, discrete      265
Choquet integral, fuzzy      441
Chromosome      434 435
Chromosome, differentiation      354
Class label      69
Class-conditional densities      26 30 32
Class-conditional distributions      30
Class-conditional distributions from an identifiable family      38
Class-conditional error rate      31
Class-conditional error rate, sampling distribution of      49
Class-conditional variance      303
Class-conscious (CC) fusion methods      430
Class-indifferent (CI) fusion methods      430
Classical binary logic      256
Classical modus ponens      258
Classifiability      176 177 179
Classification error      432 437
Classification trees      9 433
Classifier      69 70
Classifier combination      426
Classifier fusion      429
Classifier fusion by OWA      437
Classifier, minimum distance      7
Classifier, modified minimum-distance      512
Cluster analysis      7 116
Clustering      4 7 116 289 456
Clustering, possibilistic      456
Clustering, with neural networks      290
Co-occurrence matrix      178
Combined learning      28 29 44 45 54 58
Common payoff game      81 83
Compensation parameter      438
Competence      441
Competitive learning      14
Complementarity      272
Computational theory of perception (CTP)      18
Computing with words      389
Concat (concatenation) operator      568
Concept approximation      384 389
Concept description      390
Conditional attributes      384
Conjunctive rules      263
Connected word recognition      546
Consonant-vowel (CV) utterance      550
Constraint satisfaction model (CSM)      551
Context sensitivity      246
Context space      246
Context-based clustering      245
Context-free grammar      192
Context-sensitive grammar      191
Continuous action set learning automata (CALA)      76 80 88
Continuous speech recognition      548
Covariance matrix of MLE      36
Covariance matrix of MLE with unsupervised learning      40
Covariance matrix of MLE, asymptotic      41
Covariance matrix, asymptotic, supervised      42
Covariance matrix, asymptotic, unsupervised      42
Crisp (exact) set      385
Crisp class label      426
Crisp decision trees      181
Cross-validation      176
Curse of dimensionality      543
Data Mining      17
Decametric image      261
Decision attributes      384
Decision rule      69 169
Decision rule, minimal      406
Decision templates      441
Decision tree, induction      170 179
Decision tree, induction based on look-ahead      176
Decision tree, induction, look-ahead methods for      170
Decision tree, induction, node splitting criteria for      171
Decision tree, pruning      170 174
Decision tree, pruning, critical value method      175
Decision tree, pruning, error-complexity based      174
Decision tree, pruning, generalization accuracy      174
Decision tree, pruning, heuristic methods of      175
Decision tree, pruning, minimal description length based      175
Decision tree, pruning, minimum error based      175
Decision tree, pruning, stopping criteria for      174
Decision tree, top-down induction of      169
Decision tree, validation of      176
Deformable templates      148 585—588
Density estimators      7
Diffusion      99
Dirichlet distribution      122
Discriminant analysis      281
Discriminant function      72 86
Dissimilarity measure      522
Doubly stochastic models      548
Dynamic time warping (DTW) algorithm      546
Edges in an image      153
Edit distance      572
Effective frontier      457
Efficiency, logistic regression      37
Efficiency, stochastic supervision      57
Efficiency, unreliable learning      52
Efficiency, unsupervised learning      42 43
EM algorithm      33 40
EM algorithm, beta supervisor      55
EM algorithm, combined learning      44
EM algorithm, learning from stochastic supervisor      55
EM algorithm, learning from unreliable supervisor      52
EM algorithm, logistic-normal supervisor      55
EM algorithm, stochastic supervision logistic-normal model      58
EM algorithm, unsupervised learning      40
Ensemble of classifiers      425
entropy      170 172
Enumerative grammatical inference      208
Epoch sequence      553 554
Erroneous wind profiler data      305
Error complexity based pruning      174
Error function      303
Error of reduct approximation      397
Error rate      30 32 35
Error rate, distribution      32
Error rate, overall      31—33
Error rate, overall, sampling distribution      49
Error-correcting grammar      220
Error-correcting tree grammar      224
Estimator algorithms      99
evidence      441
Evolutionary computation      433
Exact probability metric      173
Extinction      434
FCM clustering      12 243 245
Feature evaluation index      478 483
Feature extraction      4 543 590
Feature matching      594
Feature selection      4 473
Feature space      3 69
features      3 4 434 590
Feedback networks      552
Feedforward networks      93
Feedforward neural networks (FFNNs)      300
Finite action set learning automata (FALA)      76
Finite mixtures      117
Finite mixtures, identifiability of      118
Finite-state automaton      193
Fisher separability criterion      5
Fitness      435
Fitness function      434
Fixed spectral dissimilarity measure      523
Formal derivative of a set of strings      204
Formal language      8 190
Formal language, alphabet of      190
Formal power series      211
Formal power series, grammatical inference      209
Formal power series, Hankel matrix of      212
Formant contours      553 554
Formants      535 543
Fourier transform, discrete inverse      544
Fourier transform, fast      306
Freeman chain code      188
Function approximation      300
fuser      104
Fuzzy c-means algorithm      12 243 245
Fuzzy class label adjustment      244
Fuzzy clustering      12 256
Fuzzy decision tree induction      181
Fuzzy densities      440
Fuzzy DYNOC algorithm      12
Fuzzy feedforward neural networks      300
Fuzzy finite automaton      200
Fuzzy grammar      9 196 198
Fuzzy integral      437 438
Fuzzy ISODATA algorithm      12
Fuzzy language      198
Fuzzy measures      256 264
Fuzzy multilayer perceptron      475
Fuzzy neurons      232
Fuzzy pattern matching      266
Fuzzy Petri net      235 238
Fuzzy Petri net, optimization of      241
Fuzzy pushdown automaton      202
Fuzzy regular grammar      199
Fuzzy rules      256
Fuzzy sets      10 230 255
G statistic      170 172
GA-classifier      351
Gaussian mixture models      547
Gene      435
Generalization      11 170 300 437
Generalized descriptors      385
Genetic algorithms (GAs)      14 179 346 433
Geometric template for objects in an image      149
Gibbs distribution      152
Gibbs distribution, internal energy function of      152
Gibbs sampling      122 138
GINI index of diversity      170 173
Glass classification problem      180
Gradient ascent algorithm      73
Gradient descent      303 312 482 487
Gradual rules      258 259
Grammatical inference      9 203
Granular computing      389
Graph theory      330
Greedy algorithm      170
ground clutter      306
Group aspiration criterion      435
Hankel matrix      212
Hastings ratio      156
Height-averaged signal power variance      309
Height-relative signal power difference      310
Hidden Markov models      548
Hierarchical Bayesian model      125
Histogram estimators      7
Hold-out methods      176
Homoscedastic normal model      28—30 32 33 36
Homoscedastic normal model, asymptotic error rate      51
Homoscedastic normal model, compared to logistic regression      36
Homoscedastic normal model, equal mixture proportions      33
Hough transform      158
Hyperspectral cube      508
Hyperspectral image      506
Hyperspectral imaging system      508
Hyperspectral remote sensing      506
ID3 algorithm      10 171
Identifiability of mixtures, multinormal family      39
Identifiability of mixtures, relation to unsupervised learning      38
Image averaging      160
Image averaging, definition of      161
Image capturing      582
Image model      148
Image model, Fourier — von Mises      160
Image morphing      159
Image segmentation      583 585
Image warping      159
Imaging spectrometer      508
Immigration      434
Imperfect supervision      28
Imperfect supervision, models      29 30
Imperfect supervision, relation to resolution of mixture      52
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