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Theodoridis S., Koutroumbas K. — Pattern recognition
Theodoridis S., Koutroumbas K. — Pattern recognition

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Название: Pattern recognition

Авторы: Theodoridis S., Koutroumbas K.

Аннотация:

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. This volume's unifying treatment covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn". A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.


Язык: en

Рубрика: Computer science/Обработка изображений/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 2nd edition

Год издания: 2003

Количество страниц: 689

Добавлена в каталог: 22.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
"Corrected" statistic      600
$l_{p}$ metric dissimilarity measures      407—408
$\Gamma$ statistic      598 604
Absolute moments      272
Acceptance interval      169
ADALINE      70
Adaptive fuzzy C-shells (AFCS) algorithm      512
Adaptive momentum      125
Adaptive resonance theory (ART2)      435
Agglomerative hierarchical algorithms      450
Akaike information criterion (AIC)      522 614
Algebraic distance      508 (See
Alternating Cluster Estimation      522
Alternating Optimization      504
Alternative hypothesis      166
Angular second moment      274
Any path method      363
Autoregressive processes      287
Autoregressive-moving average (ARMA(p, m))      287
Average expected quantization error      534
Average partition density (PA)      619
Average partition shell density      620
Average risk      17
Backpropagation algorithm      110 104
Basic competitive learning algorithm      554
Basic sequential algorithmic scheme (BSAS)      433
Basis images      209
Basis images (matrices)      209
Basis sequences      229 243
Basis vectors      208
Baum — Welch reestimation      367
Bayes classification rule      14
Bayes decision theory      13
Bayes rule      13
Bayesian inference      32
Bayesian information criterion (BIC)      614
Bellman's optimality principle      324
Bending energy      302
Best path method      365
Between-class scatter matrix      179
Bhattacharyya distance      177
Bias-Variance dilemma      76
Binary morphology based clustering algorithm (BMCA)      571
Biorthogonal expansion      243
Biorthogonality condition      245
Boosting      See "Combining classifiers"
Bootstrapping techniques      594
Boundary detection algorithms (BDA)      432
Branch and bound      186
Branch and bound clustering (BBC) algorithm      562 432
Branch and bound methods      561
c-means algorithm      See "Isodata algorithm"
Center of mass      301
Central moments      271
Centroid condition      535
Chain codes      298
Chaining effect      457
Channel equalization      356
Characteristic functions      404 644
Chernoff bound      177
Circular backpropagation model      126
Classification error probability      16
Classification tree      561
Classifier combining      See "Combining classifiers"
Classifiers      3
Closing      567
Cluster      397 402
Cluster detection algorithm for discrete valued sets (CDADV)      569
Cluster validity      591
Cluster variation      617
Cluster, compact      489
Cluster, linear-shaped      489
Cluster, ring-shaped      489 497
Cluster, shell-shaped      489
Cluster, spherical      517
Clustering      402—404 429
Clustering criterion      397 399
Clustering hypothesis      575
Clustering tendency      399 591 624
Co-occurrence      273
Co-occurrence matrices      272
Code vector      533 (See
Combining classifiers      150
Compactness and separation validity function      617 (See
Competitive learning algorithms      552—560
Competitive learning associated with cost functions      558
Complete link      455 469
Computer storage utilization      533
Computer-aided diagnosis      2
Concordant pair      603
Confusion matrix      496 506
Conjugate gradient      664
Conscientious competitive learning algorithms      556
Constrained optimization      664
Constraints      335
Constructive techniques      102
Context-dependent classification      351
Contingency table      410
Continuous observation HMM      370
Continuous speech recognition      329
contrast      274
Convex functions      667
Convex hull      625
Convex programming      674
Convex sets      668
Cophenetic correlation coefficient (CPCC)      602
Cophenetic distance      476
Cophenetic matrix      477
Correlation      66
Cost function      489
Covariance matrix      20
Cox — Lewis test      630
Crisp clustering algorithms      432 (See
Critical interval      166
Cross-correlation      66
Cross-correlation coefficient      338
Cross-entropy      115 372 647
Crossover      461
Cumulants      221 645
Curse of dimensionality      43 134
Curvature features      300
Data compression      400 533
Data normalization      165
Data reduction      400
Davies — Bouldin (DB) index      612—613
Davies — Bouldin-like indices      612—613
Decision surfaces      19
Decision trees      143
Decomposition layers      630
Deformable template matching      343
Delta-bar-delta      113
Delta-delta rule      113
Dendrogram      452 (See
Deterministic annealing      580—581
Diameter of a cluster      610
Dilation      565
Directed graphs      464
Directed path      550
Directed tree      550
Direction length features      299
Discordant pair      603
Discrete binary (DB) set      564
Discrete cosine      230
Discrete cosine transform (DCT)      230
Discrete Fourier Transform      226
Discrete observation HMM models      366
Discrete sine transform (DST)      231
Discrete time wavelet coefficients      243
Discrete time wavelet transform      239
Discrete wavelet frame      260
Discriminant functions      19
Dispersion of a cluster      612
Dissimilarity matrix      451
Dissimilarity measure between points      423 425
Dissimilarity measure between sets      406 423
Distance between a point and a quadratic surface algebraic distance      508
Distance between a point and a quadratic surface normalized radial distance      510
Distance between a point and a quadratic surface perpendicular distance      508
Distance between a point and a quadratic surface radial distance      509
Distortion function      534
Distortion measure      534
Divergence      174
Divisive hierarchical algorithm      477 450 480
Dunn index      610
Dunn-like indices      610—611
Dynamic programming      186 324
Dynamic similarity measures      413
Dynamic time warping      329
Eccentricity      301
Edge connectivity      467
Edgeworth expansion      223 646
Edit distance      325
EM-algorithm      491
Empirical classification error      193
End point constraints      333
entropy      34 213 272 275
Erosion      565
Error counting approach      385
Euclidean distance      25 405
Expectation Maximization (EM) algorithm      36
External criteria      592 595—601
Feature selection      163 398
Feature vectors      3
features      3
Features, interval scaled      401
Features, nominal      401
Features, ordinal      401
Features, ratio scaled      401
Finite state automation      361
First-order statistics features      270
Fisher's discriminant ratio      181
Fisher's linear discriminant      190
Floating search methods      185
Fourier descriptors      296
Fowlkes and Mallows index      598
Fractal dimension      303
Fractals      303
Fractional Brownian motion sequences      307
Frobenius norm      217
Fukuyamma — Sugeno index (FS)      618
Fuzzifier      501
Fuzzy approaches      490 (See
Fuzzy average shell thickness      620
Fuzzy c + 2 means algorithm      522
Fuzzy C ellipsoidal shells (FCES) algorithm      515
Fuzzy C plano-quadric shells (FCPQS)      517
Fuzzy C quadric shells (FCQS) algorithm      516
Fuzzy c-Means (FCM) algorithm      505
Fuzzy c-varieties (FCV) algorithm Fuzzy covariance matrix      618
Fuzzy density      619
Fuzzy hypervolume      618
Fuzzy measures      415
Fuzzy shell adaptive fuzzy C-shells (AFCS) algorithm      512—513
Fuzzy shell clustering algorithms      512—517
Fuzzy shell covariance matrix      620
Fuzzy shell density      620
Fuzzy shell fuzzy C ellipsoidal shells (FCES) algorithm      512 515 541
Fuzzy shell fuzzy C plano-quadric shells (FCPQS)      517
Fuzzy shell fuzzy C quadric shells (FCQS) algorithm      515—516 541
Fuzzy shell modified fuzzy C quadric shells (MFCQS) algorithm      515—516 541
Gabor filter      260
Gabriel graphs (GG)      550 611 613
Gauss — Newton method      506
Generalized agglomerative scheme (GAS)      450
Generalized competitive learning scheme (GCLS)      554
Generalized divisive scheme (GDS)      478
Generalized fuzzy algorithmic scheme (GFAS)      504
Generalized hard algorithmic scheme (GHAS)      530
Generalized linear classifiers      127
Generalized mixture decomposition algorithmic scheme (GMDAS)      492
Generalized possibilistic algorithmic scheme (GPAS)      525
Generalized XB index      617
Genetic algorithms      432 545 582
Genetic algorithms crossover      582
Genetic algorithms mutation      582
Genetic algorithms reproduction      582
Geometric moments      281
Gibbs random fields      377
Global constraints      325 333
Global convergence theorem      522
Grade of membership      403
Gradient descent algorithm      57 106 659
Graph complete      546
Graph edges      464 546
Graph inconsistent edges      546
Graph theory-based algorithmic scheme (GTAS)      467
Graph vertices      464
Gray level run lengths      275
Gustafson — Kessel (G-K) algorithm      517
Haar transform      233 249
Hadamard transform      231
Hamming distance      410—411
Hard clustering      491
Hard clustering algorithms      529
Hidden Markov models      361
Hierarchical agglomerative algorithms      431
Hierarchical clustering algorithms      431
Hierarchical divisive algorithms      431
Hierarchical search      341
higher order      126
Holdout method      388
Hopkins test      629
Hubert's $\Gamma$ statistic      598 (See
Hughes phenomenon      196
Hurst parameter      308
Hypercube      521
Hypersphere      595
Hypothesis generation      400
Hypothesis testing      400 592—605
Images      207
Incomplete data set      36
Independent component analysis (ICA)      219
Information theoretic clustering      584
Information theory based criteria      584 613 614
Inner product      408
Internal criteria      592 595 602—605
Interpoint distances      628
Interpretation of clustering results      399
Intersymbol interference      356
Inverse difference moment      275
ISODATA algorithm      532
Isolated word recognition      329
Itakura constraints      333 334
Itakura — Saito distortion      555
Jaccard coefficient      598
k Nearest Neighbor density estimation      43
K-means algorithm      See "Isodata algorithm"
Karhunen — Loeve transform      210
Karush — Kuhn — Tucker (KKT) conditions      84 669
kernels      41
Kesler's construction      64
Kullback — Leibler distance      176 223 647
kurtosis      226 271 645
Lagrange multipliers      665
LBG algorithm      535
Leaky learning algorithm      556
Learning subspace methods      214
Least squares methods      65
Leave-one-out method      388
Levenberg — Marquardt (L-M) method      506
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