|
|
 |
| Авторизация |
|
|
|
| Поиск по указателям |
|
|
|
|
|
|
|
 |
|
|
|
| Farhang-Boroujeny B. — Adaptive filters: theory and applications |
|
|
|
| Предметный указатель |
Fast transversal recursive least-squares (FTRLS) algorithms, computational complexity 461
Fast transversal recursive least-squares (FTRLS) algorithms, derivation of 461—464
Fast transversal recursive least-squares (FTRLS) algorithms, forgetting factor, range of 466
Fast transversal recursive least-squares (FTRLS) algorithms, normalized gain vector 461 463 464
Fast transversal recursive least-squares (FTRLS) algorithms, numerical stability 460 466
Fast transversal recursive least-squares (FTRLS) algorithms, rescue variable 466
Fast transversal recursive least-squares (FTRLS) algorithms, soft initialization 466
Fast transversal recursive least-squares (FTRLS) algorithms, stabilized FTRLS algorithm 460 466
Fast transversal recursive least-squares (FTRLS) algorithms, summary 468
Filter structures see "Adaptive filter structures"
Filter, defined 1
Filter, linear see "Linear filters"
Finite impulse response (FIR) filters 5 321 see "Wiener
Forgetting factor 419
Forward linear prediction 357—359 see
Forward linear prediction, fast recursive algorithms and 439
Forward linear prediction, relations between backward prediction and 361
Forward linear prediction, Wiener equation for 358
Forward prediction error 358
Forward prediction-error filter 362
Fractionally lap-spaced equalizer 346 348
Frequency bin adaptive filtering 265
Frequency bin filter 268
Frequency components 1
Frequency domain adaptive filters 9
Frequency response 35
FTF algorithm see "Fast transversal filters"
Gaussian moments expansion formulae 179 199
Generalized formulation of the LMS algorithm 472—473
Generalized formulation of the LMS algorithm, algorithms covered 473
Generalized formulation of the LMS algorithm, analysis 473—477
Generalized formulation of the LMS algorithm, analysis, excess MSE 476
Generalized formulation of the LMS algorithm, analysis, minimum MSE 479
Generalized formulation of the LMS algorithm, analysis, misadjustment 476
Generalized formulation of the LMS algorithm, analysis, noise and lag disadjustments 477
Generalized formulation of the LMS algorithm, stability 479
Generalized formulation of the LMS algorithm, step-size parameters 473
Generalized formulation of the LMS algorithm, step-size parameters, bounds on 478
Gradient operator 83 121 140 326
Gradient vector 54 121
Gradient vector, instantaneous 121 248
Gradient vector, instantaneous, average of 249
Gradient with respect to a complex variable 60
Group-delay 309 311 315
Hand-free telephony 247
Hardware implementation 320 388
Hermitian 62
Hermitian form 91
Hermitian matrices, eigenanalysis of see "Eigenanalysis"
Hermitian matrix 90
Hybrid circuits 21
Hyper-ellipse 110 213 214
Hyper-paraboloid 110 113
Hyper-spherical 213 214
I1R adaptive line enhancement 334—343
I1R adaptive line enhancement, adaptation algorithms 337—339
I1R adaptive line enhancement, adaptive line enhancer (ALE) 334
I1R adaptive line enhancement, Cascaded structure 342
I1R adaptive line enhancement, computer simulations 340—343
I1R adaptive line enhancement, MATLAB programs 342
I1R adaptive line enhancement, notch filtering 335
I1R adaptive line enhancement, performance functions 335—336
I1R adaptive line enhancement, transfer function 334
Ideal LMS Newton algorithm 210 see
Identification applications 10—11
Impulse invariance, method of 349
Independence assumption 142 260 284 287 472
Independence assumption, validity of 143 159
Infinite impulse response (I1R) adaptive filters 323 see "Magnetic
Infinite impulse response (I1R) adaptive filters, computational complexity 323
Infinite impulse response (I1R) adaptive filters, equation error method 323 330—333 346 348
Infinite impulse response (I1R) adaptive filters, equation error method, block diagram 330
Infinite impulse response (I1R) adaptive filters, output error method 323 324—329
Infinite impulse response (I1R) adaptive filters, output error method, block diagrams 328
Infinite impulse response (I1R) adaptive filters, output error method, LMS recursion 327
Infinite impulse response (I1R) adaptive filters, output error method, summary of LMS algorithm 329
Infinite impulse response (I1R) adaptive filters, relationship between equation error method and output error method 331
Infinite impulse response (I1R) adaptive filters, stability 323
Infinite impulse response (I1R) filters 5 323 see "Wiener
Innovation process 386
Interference cancellation 21—27 see
Interference cancellation, primary and reference inputs 21
Interpolation 296 see "Mulltrate
Intersymhol interference (ISI) 12 71 351
Inverse Levinson — Durbin algorithm 375 387
Inverse modelling 11
Inverse modelling applications 11—15
Inversion integral for the z-transform 33
Iterative search method 3 121
Joint-process estimation 49 372 377
Karhunen — Loeve expansion 99
Karhunen — Loeve Transform (KLT) 98 210 214 219 473
Lagrange multiplier 174 184 185
Lattice filters see also "Adaptive lattice filter"
Lattice filters, all-pole 379—380
Lattice filters, all—zero (lattice joint-process estimator) 371—372
Lattice filters, conversion between lattice and transversal predictors 373—375
Lattice filters, derivations, all-pole 379—380
Lattice filters, derivations, joint process estimator (all-zero) 371—372
Lattice filters, derivations, pole-zero 380—381
Lattice filters, derivations, predictor 364—370
Lattice filters, order-update equation for the mean-square value of the prediction error 369
Lattice filters, order-update equations for prediction errors 357 364 368
Lattice filters, orthogonalization, property of 370—371
Lattice filters, orthogonalization, property of, transform domain adaptive filters and 370
Lattice filters, partial correlation (PARCOR) coefficients 367 372
Lattice filters, pole-zero 380
Lattice filters, system functions 372—373
Lattice joint-process estimator 371—372
Lattice order-update equations 357 364 368
Lattice-based recursive least-squares algorithms see "Recursive least-squares lattice algorithms"
Leaky LMS algorithm 195
Learning Curve 128 146—149 427—430 433
Least-mean-square (LMS) algorithm 7 139
Least-mean-square (LMS) algorithm, average tap-weights behaviour 141—144
Least-mean-square (LMS) algorithm, bounds on the step-size parameter 143 156 180
Least-mean-square (LMS) algorithm, compared with recursive least-squares algorithms 431 473
Least-mean-square (LMS) algorithm, complex-valued case see "LMS algorithm for complex-valued signals"
Least-mean-square (LMS) algorithm, complexity 141
Least-mean-square (LMS) algorithm, computer simulations 157—169
Least-mean-square (LMS) algorithm, computer simulations, adaptive line enhancement 164—166 see
Least-mean-square (LMS) algorithm, computer simulations, beamforming 166—169 see
Least-mean-square (LMS) algorithm, computer simulations, channel equalization 159—164 see
Least-mean-square (LMS) algorithm, computer simulations, comparison of learning curves of modelling and equalization problems 163
Least-mean-square (LMS) algorithm, computer simulations, MATLAB programs 157 159 161 166 169
Least-mean-square (LMS) algorithm, computer simulations, system modelling 157—159
Least-mean-square (LMS) algorithm, convergence analysis 141—156
Least-mean-square (LMS) algorithm, derivation 139—141
Least-mean-square (LMS) algorithm, eigenvalue spread and 143
Least-mean-square (LMS) algorithm, excess mean-square error and misadjustment 152—154
Least-mean-square (LMS) algorithm, frequency dependent behaviour of 201
Least-mean-square (LMS) algorithm, improvement factor 217
Least-mean-square (LMS) algorithm, independence assumption 142
Least-mean-square (LMS) algorithm, initial tap weights on transient behaviour of effect of 156
Least-mean-square (LMS) algorithm, lap-weight vector, perturbation of 152
Least-mean-square (LMS) algorithm, learning curve 146—149
Least-mean-square (LMS) algorithm, learning curve, numerical examples 148
Least-mean-square (LMS) algorithm, learning curve, time constants 149
Least-mean-square (LMS) algorithm, mean-square error behaviour 144—156
Least-mean-square (LMS) algorithm, misadjustment equations 153—154
Least-mean-square (LMS) algorithm, modes of convergence 143
Least-mean-square (LMS) algorithm, power spectral density and 143
Least-mean-square (LMS) algorithm, robustness 141
Least-mean-square (LMS) algorithm, stability analysis 154—156
Least-mean-square (LMS) algorithm, steepest-descent algorithm and 141 143
Least-mean-square (LMS) algorithm, summary 141
Least-mean-square (LMS) algorithm, tap-weight misalignment 196 435
Least-mean-square (LMS) algorithm, tracking behaviour 473 481 482 485
Least-mean-square (LMS) algorithm, trajectories, numerical example of 145
Least-mean-square (LMS) algorithm, weight error correlation matrix 149—152 see "Names
| Least-squares backward prediction 442—443 see
Least-squares backward prediction, a posteriori and a priori prediction errors 442
Least-squares backward prediction, conversion factor 451
Least-squares backward prediction, gain vector 443
Least-squares backward prediction, least-squares sum of the estimation errors 442
Least-squares backward prediction, normal equations of 442
Least-squares backward prediction, standard RLS recursion for 443
Least-squares backward prediction, transversal predictor 442
Least-squares estimation 7 413 see "Fast
Least-squares estimation, curve fitting interpretation of 413 436
Least-squares estimation, Forgetting factor 419
Least-squares estimation, formulation of 414—415
Least-squares estimation, minimum sum of error squares 415
Least-squares estimation, normal equation 415
Least-squares estimation, orthogonal complementary projection operator 419
Least-squares estimation, principle or orthogonality 416—417 441 443 445
Least-squares estimation, principle or orthogonality, corollary to 417
Least-squares estimation, principle or orthogonality, interpretation in terms of inner product of vectors 417
Least-squares estimation, projection operator 418—419
Least-squares estimation, relationship with Wiener filter 413
Least-squares estimation, weighted sum or error squares 414
Least-squares estimation, weighting function 413
Least-squares forward prediction 440—442 see
Least-squares forward prediction, a posteriori and a priori prediction errors 441
Least-squares forward prediction, conversion Factor 451
Least-squares forward prediction, gain vector 441
Least-squares forward prediction, least-squares sum of the estimation errors 440
Least-squares forward prediction, normal equations of 440
Least-squares forward prediction, standard RLS recursion for 441
Least-squares forward prediction, transversal predictor 440
Least-squares lattice 443—446 see
Least-squares lattice, computation of PARCOR coefficients 445
Least-squares lattice, computation of regressor coefficients 446
Least-squares lattice, least-squares lattice joint process estimator 444
Least-squares lattice, partial correlation (PARCOR) coefficients 443
Least-squares lattice, principle of orthogonality 445
Least-squares lattice, properties of 445
Least-squares lattice, regressor coefficients 443
Least-squares, method of see "Least-squares estimation"
Levinson — Durbin algorithm 357 375—377
Levinson — Durbin algorithm, extension of 377—379
Linear estimation theory see "Wiener filters"
Linear filtering theory see "Wiener fillers"
Linear filters, defined 2
Linear filters, transmission of a stationary process through 42—45
Linear least-squares estimation see "Least-squares estimation"
Linear least-squares filters see "least-squares estimation"
Linear multiple regressor 425 471
Linear prediction 15
Linear prediction, lattice predictors see "Lattice predictors"
Linear prediction, M-step-ahead 164
Linear prediction, one-step ahead 357
Linear predictive coding (LPC) 19
Linearly constrained LMS algorithm 184—188
Linearly constrained LMS algorithm, excess MSE due to constraint 185
Linearly constrained LMS algorithm, extension to the complex-valued case 186—187
Linearly constrained LMS algorithm, Lagrange multiplier and 184 186
Linearly constrained LMS algorithm, minimum mean-square error 185
Linearly constrained LMS algorithm, optimum lap-weight vector 185
Linearly constrained LMS algorithm, summary 186
LMS algorithm see "Least-mean-square algorithm"
LMS algorithm for complex-valued signals 178—180
LMS algorithm for complex-valued signals, adaptation recursion 179
LMS algorithm for complex-valued signals, bounds on the step-sire parameter 180
LMS algorithm for complex-valued signals, complex gradient operator 178
LMS algorithm for complex-valued signals, convergence properties 179
LMS algorithm for complex-valued signals, misadjustment equation 179
LMS recursion 141
LMS-Newton algorithm 210 388 430 see
LMS-Newton algorithm, tracking behaviour 473 479 481 482
Low-delay analysis and synthesis filter banks 309—311
Low-delay analysis and synthesis filter banks, design method 309—311
Low-delay analysis and synthesis filter banks, design procedure 314—315
Low-delay analysis and synthesis filter banks, numerical example 315—317
Low-delay analysis and synthesis filter banks, properties of 311—314
M-step-ahead predictor 164
Magnetic recording 14—15 324
Magnetic recording, class IV partial response 15 345
Magnetic recording, dibit response 14 344 351
Magnetic recording, equalizer design for 344—352
Magnetic recording, equalizer design for, MATLAB program 352
Magnetic recording, equalizer design for, numerical results 350—352
Magnetic recording, equalizer design for, Wiener — Hopf equation 347
Magnetic recording, head and medium 14
Magnetic recording, impulse response 14
Magnetic recording, Lorentzian pulse 14 344
Magnetic recording, pulse width 14 344
Magnetic recording, recording density 14 344
Magnetic recording, recording track 14
Magnetic recording, target response 15 344
Magnetic recording, temporal and spatial measure 14
Matrix, trace of 93 154
Matrix-inversion lemma 153 421
Maximally spread signal powers 214 219
Maximum-likelihood detector 11
Mean-square error (MSE) 50
Mean-square error (MSE), excess MSE see "Names of specific algorithms"
Mean-square error (MSE), minimum 54 58 62 67
Mean-square error criterion 50
Measurement Noise 68
Minimax theorem 94 166 214 219
Minimax theorem, eigenanalysis of particular matrices, in 101 116
Minimum mean-square error 54 58 62 67
Minimum mean-square error criterion 49
Minimum mean-square error derivation, direct 53
Minimum mean-square error derivation, using the principle of orthogonality 58
Minimum mean-square prediction error 359 360
Minimum sum of error squares 415 444
Misadjustment see "Names of specific algorithms"
Modelling 10—11 125 157 471
Modem 13
Modes of convergence see "Names of specific algorithms"
Moving average (MA) model 15
Multidelay fast block LMS (FBLMS), algorithm 265
Multipath communication channel 489
Multipath communication channel, fade rate 490
Multirate signal processing 293 see "DFT "Low-delay "Subband
Multirate signal processing, analysis filter bank 293 294
Multirate signal processing, decimation 294
Multirate signal processing, interpolation 296
Multirate signal processing, subband and full-band signals 295
Multirate signal processing, synthesis filter bank 293 297
Multirate signal processing, weighted overlap—add methods 295—298
Multivariate random-walk process 472
Mutually exclusive spectral hands, processes with 205
Narrow-band adaptive fillers see "Adaptive line enhancement"
Narrow-band signals 78
Newton’s method/algorithm 132—133 210
Newton’s method/algorithm, correction to the gradient vector 132
Newton’s method/algorithm, eigenvalues and 134
Newton’s method/algorithm, eigenvectors and 134
Newton’s method/algorithm, interpretation of 134—135
Newton’s method/algorithm, Karhunen — Loeve transform (KLT) and 134
Newton’s method/algorithm, learning curve 133
Newton’s method/algorithm, mode of convergence 133
Newton’s method/algorithm, power normalization and 134
Newton’s method/algorithm, stability 133
Newton’s method/algorithm, whitening process in 135
Noise cancellation 75—81
Noise cancellation, noise canceller set-up 76
Noise cancellation, power inversion formula 78
Noise cancellation, primary and reference inputs 75
Noise cancelling, adaptive see "Active noise control" "Noise
Noise enhancement, in equalizers 12 74
Non-negative definite correlation matrix 90
Non-stationary environment see "Tracking"
Normalized correlation 367
Normalized least-mean-square (NLMS) algorithm 172—176 317
Normalized least-mean-square (NLMS) algorithm, constrained optimization problem, as a 173
Normalized least-mean-square (NLMS) algorithm, derivation 172
|
|
|
| Реклама |
|
|
|
|
|
О проекте