Katayama T., Sugimoto S. — Statistical Methods in Control and Signal Processing :: Электронная библиотека попечительского совета мехмата МГУ

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Katayama T., Sugimoto S. — Statistical Methods in Control and Signal Processing

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Название: Statistical Methods in Control and Signal Processing

Авторы: Katayama T., Sugimoto S.

Аннотация:

This readily accessible volume documents the latest developments in statistical modeling, identification, estimation, and signal processing, presenting state-of-the-art statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas.

Язык:

Рубрика: Математика/Численные методы/Вейвлеты, обработка сигналов/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1997

Количество страниц: 553

Добавлена в каталог: 04.03.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

Log-likelihood      42 55—56 414 459
Low-pass approximation      162
Lyapunov equation      3
Lyapunov’s convexity theorem      309
M-function      441
Majority voting rule      472
Maneuvering target tracking      448
MAP (maximum a posteriori) criterion      415
MAP (maximum a posteriori) estimate or estimator      218 404—405 414—416
MAP (maximum a posteriori) nonlinear recursive filtering      217
MAP (maximum a posteriori) parameter estimation      413
MAP (maximum a posteriori) technique      403
MAP-NSF (noise subspace fitting) method      416—421 423—424
Markov chain      286—287
Markov chain aperiodic      530—531
Markov chain homogeneous      526—527 530
Markov chain irreducible      530
Markov parameters      131 132
Markov process      1 94 274 286
Markov process controlled      94
Markov process Gaussian      485
Markov random field (MRF)      525—526 see
Markov — Poisson parameters      133 135 140
Matrix minimum principle      262
Matrix perturbation theory      191
Maximal correlation      108
Maximization criterion multistage      379 383
Maximization criterion single-stage      384
Maximum entropy method (MEM)      442 444
Maximum likelihood (ML)      86 91
Maximum likelihood criterion, regularized      415
Maximum likelihood estimate or estimator      42 65 367 371
Maximum Likelihood Estimation      86
Maximum likelihood method      459
Maximum likelihood solution      401
Maximum likelihood structured      413
Maximum likelihood type II      40
Membership function      300 315
Memory      95—96
Methods of moments      30
Metropolis algorithm      525 527—529
Metropolis-like sampling algorithm      528
Minimax filtering problem      243—244
Minimum entropy deconvolution      379
Minimum variance distortionless response (MVDR)      412—413
Model abrupt seasonal      61
Model abrupt trend      61
Model black-box polynomial      125
Model discrete-time impulse response (DTIRM)      150
Model errors-in-variables      355 357
Model input-output      11
Model linear-in-parameters      128
Model Markov parameter      131—132
Model parametric form of continuous-time      125
Model random perturbation      406
Model reduction      85
Model structure selection, objective      97
Model time-moment      137—140
Model trend      43 59
Model urn, Polya-like      279
Modeling Bayesian      37
Modeling continuous-time      122
Modeling gray-box      129
Modeling hierarchical      464
Modeling non-Gaussian      65
Modeling state space      37 41
Modeling symmetric      355
Modeling time-series      43
Modeling vibrating system      109—112
Modulated autocovariance      329
Monte Carlo approach      38 57
Monte Carlo filtering methods      59 61
Monte Carlo methods      56 57
Monte Carlo simulation      101—102 516
Morphological computation process      503
Moving-average (MA) model      132
Moving-average model, generalized (GMAM)      121 129
Multichannel blind deconvolution      375—376 379
Multichannel blind deconvolution, necessary and sufficient condition for      388
Multilevel logistic model (MLL)      533—534 541
Multirate systems      341
Multiresolution analysis or approximation      154
Multitarget tracker      447
MUSIC (Multiple Signal Classification)      401—402 410—411 442 444—446
Narrowband modeling assumptions      404
Neighborhood system      526
Neural networks      481
Neural networks multiresolution (MRNN)      152 159—161
Neural networks stochastic binary      481
Neutrality      280
Noble identities      342
Noise subspace fitting (NSF)      411 416 see
Nonbound approach      462 464
Noncausal system      376
Nonminimum phase system      375
Nonstationarity in the mean      42
Nonstationary binary process      68
Nonstationary time-series      43
Nuisance parameters      403 405
Null hypothesis      187—190 197 202
Numerical approximation      55
Oblique projection      20
Observability      436
Observability Gramian      437—438
Observability matrix, extended      185
Onsager — Machlup functional      218—219
Order statistics      277 296
Order statistics of the market shares      275
Orthogonal projection      7 410
Output error (OE)      126
Parallel distributed scheme or system      502 508
PARCOR (partial autocorrelation) coefficients      49 52 66 67
Partition function      527
Periodic AR process      335
Periodic AR process, spectral formula of      336
Persistently exciting      368
Phase transition phenomenon      525—526 535
Polyphase representation      343 347
Polyspectrum      360
Polyspectrum integrated      356—360 363
Positive real      31
Positivity      29 31
Potential      527
Prediction      41 54 56—57
Prediction error method      459 469
Prediction nonlinear      108
Predictive mapping layer      486—491
Predictor spaces      18
Predictor spaces oblique      21
Process monitoring      112
Pseudo-inverse      11 410
Pseudo-log-likelihood (PLL) method      533 535 540
Quasi-ARMAX model      465—466
Quasi-ARMAX model hybrid      467—468 474
Quasi-periodic model or process      70
Radar antenna      399
Radar cross-section (RCS)      442
Radar Doppler weather      433—434 see
Radar imaging      433
Radar parameter      445
Radar tracking      433
Radial basis function (RBF) network      151 158
Random partitions      274 282
Random partitions, exchangeable      296

Random patterns      502
Random variable, i.i.d.      277 357 378
Rank test Gramian-based (GRAB)      201 207 212
Rank test Gramian-based multivariable      208
Rank test(s)      187—188 196 200 208
Rank test, based on EVD      188
Rank test, based on LDU decomposition      200
Rank test, comparison and evaluation of      208—215
Rational extension      29—30
Realization      4 14
Realization algorithm, eigensystem (ERA)      109—111 149
Realization ARMA model      134 138
Realization deterministic      19 26
Realization finite-interval      24
Realization minimal      3 19
Realization minimal partial      29
Realization minimum state-space      182
Realization state space      1
Realization stationary      18
Reduced-order functional estimator      259
Redundant parameter vector      464
Relative frequency      528—529
Resolution enhancement      442
Riccati difference equation      241 245
Robbins — Monro method      481
Robustness issues      402
Sampling algorithm or method      535
Scaling function      155 159
Scaling function Haar      159
Scaling function Meyer      155—156
Scattering theory, Lax — Phillips      15
Seasonal adjustment      46
Seasonal component      43—47
Seasonal component non-Gaussian      61
Seismic data      52 63
Self-similar pattern      499 501 507 520
Self-similar pattern experiments      516—521
Self-similarity      499
Self-similarity mappings      501
Sensor position errors      407
Sequential estimation, statistical      481
Shalvi — Weinstein approach      375 379
Shierpinski gasket      501
Signal estimation      412
Signal processing in radar system      431
Signal separation, blind      375
Signal subspace fitting (SSF) algorithm      420
Similarity      see also Self-similarity
Similarity contour      504
Similarity function      503
Singular value      437
Singular value decomposition (SVD)      87 92 203 444 446
Singular value decomposition generalized      92—93
Singular value Hankel      149
Smoother, fixed-lag      58 418
Smoothing      42 54 56—58
Smoothing error      27
Smoothing nonlinear      73
Smoothness criterion      40
Smoothness priors      39—41 50
Soft bound      454
Soft bound approach      458
Spectral density matrix      2 181
Spectral density matrix, cyclic      327 333 346
Spectral factor      2
Spectral factorization theorem      181
Splitting subspace (minimal) oblique      21 23
Splitting subspace Markovian      14—18 25
State space model      45 92
State space model, estimation      95—97
State space model, general      54
State space model, nonlinear      73
Stationary process      1 359
Stationary process M-channel weakly      331
Statistical decision making      439
Stochastic approximation      481
Stochastic binary tree search      487
Stochastic embedding approach      458
Stochastic mapping      485
Stochastic realization      1
Stochastic realization, classical      2
Stochastic realization, geometric      4
Stopping time      484
Stopping variable, extended      483—484
Strong cut      300
Strongly consistent      365
Subspace (-based) methods      32 409
Subspace (-based) methods, statistical properties of      32
Subspace corrected (SC) MVDR      413
Subspace decomposition algorithm, fast      100
Subspace fitting      402
Subspace fitting signal (SSF)      402 411
Subspace fitting weighted      402
Subspace identification      5 29
Subspace(s) corrected (SC) algorithm      403
Subspace, past and future      10
Summability conditions      359
Summability conditions, absolute      377
Supervised learning      481
System analysis      432
System identification      85 see
System identification in continuous-time domain      124
System identification, automatic      84
System identification, structure of      84
System identification, subspace-based state space (4SID)      99 180
System identification, transfer function matrix      365
System identification, using polyspectra      355
Terminal Doppler weather radar (TDWR)      433 439 441 449
Threshold      482—483
Time-moment sequence      137 139
Time-varying variance      62
Toeplitz matrix      8 30
Toeplitz matrix, block      183
Trade-off analysis      432
Transfer function matching      367
Transition probability      527 530—532
Trapezoidal approximation      122
Trispectrum      361
Truth function or value      300 307—308
Tufts — Kumaresan method      442
Unbiasedness      261
Under-modeling      127
Unmodeled dynamics      122 454 457 462 469
Unmodeled dynamics, index of      470
Unobservable space      437
Unstructured errors      408 419
Vague perception      300 304
Vague perception of random phenomena      299
Variance error      161
Wavelet      155
Wavelet neural network (WNN)      157—159
Wavelet transformation      151
Weierstrass theorem      179
White Gaussian process      436 442
White noise or process      1 41
White noise or process, finitely additive      217—218
White noise or process, Gaussian      39 42 209 243 455
Whitening condition, normalized      378 384
Wing flutter      114—115
Wold decomposition theorem      15
Wolfer sunspot data      71
Yule — Walker (-type) equation      190 206 335
Zakai equation      218 227
Zipf’s law      293

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