Index
a
- abundance
- access point
- active learning
- adaptive filtering
- adaptive kernel learning
- additive noise
- additive noise model
- alternative hypothesis
- analysis equation
- anomaly change detection
- anomaly detection
- antenna array
- anti‐causal systems
- array processing
- audio
- audio compression
- autocorrelation
- autocorrelation‐induced kernel, autocorrelation kernel
- autocorrelation kernel
- autocorrelation matrix
- autoregressive (AR)
- autoregressive and moving average (ARMA)
- autoregressive and exogenous (ARX)
b
- bag of words features
- bag of words kernel
- band‐pass
- bandwidth
- base‐band representation
- basis
- basis pursuit
- Bayesian nonparametric
- Bernoulli–Gauss distribution
- Bernoulli process
- bias–variance dilemma
- bi‐exponential distribution see Laplacian noise
- big data
- biomedical signals
- biophysical
- bit error rate (BER)
- Blackman–Tukey correlogram
- blind source separation (BSS)
- Bootstrap resampling
- B‐scan
- Burg’s method
- butterfly algorithm
c
- canonical basis
- cardiac mesh
- cardiac navigation systems
- cardiac signal
- cardiag image
- Cauchy–Schwartz inequality
- Cauchy sequence
- causal systems
- centering
- change detection
- change vector analysis
- channel estimation
- chaotic
- Choi–Williams distribution
- Cholesky decomposition
- Cholesky factorization
- chronocrome
- classification
- clustering
- codebook
- collinearity
- color image
- communication
- complex algebra
- complex envelope
- complex exponential
- complexification trick
- complex signal
- composite kernel
- compressed sensing
- confidence interval (CI)
- constrained covariance (COCO)
- continuous‐time equivalent system for nonuniform interpolation
- continuous‐time signals
- convex
- convolution
- convolution (multidimensional)
- correlation
- correlogram
- cost function
- covariance function
- covariance operator
- covariate shift
- cross‐correlation
- cross‐covariance
- cross‐information
- cross‐validation
- CUSUM
d
- deal effect curve
- decision tree
- deconvolution
- denoising
- determination coefficient
- dictionary learning
- digital filtering
- dimensionality reduction
- Dirac delta
- direction of arrival (DOA)
- discrete cosine transform (DCT)
- discrete‐time signals
- domain adaptation
- domain description
- dot product
- double side band
- dual parameters
- dual representation
- dual signal model (DSM)
e
- eigenfunctions
- electric networks
- electroanatomic map (EAM)
- electrocardiogram (ECG)
- electroencephalogram (EEG)
- elliptical
- empirical kernel map
- empirical risk
- endmember
- energy
- energy spectral density
- equalization
- Euclidean distance
- Euclidean divergence
- Euler–Poincaré formula
- evidence
- expectation–maximization
- eye diagram
f
- feature map
- feature mapping
- feature space
- feedback
- filter
- filter bank analysis
- filtering
- finite impulse response (FIR)
- Fisher discriminant
- Fourier coefficients
- Fourier transform
- fractal
- free parameters
- frequency
- functional analysis
- function approximation
- fuzzy
- fuzzy clustering
g
- Gabor transform
- gamma distribution
- gamma‐filter
- gamma function
- Gaussian distribution
- Gaussian mixture model (GMM)
- Gaussian mixtures
- Gaussian noise
- Gaussian processes
- generative kernel
- genetic
- Gram matrix
- graph
- graph Laplacian
- graph Laplacian matrix
- Grassman–Stiefel manifold
- grayscale image
- greedy algorithms
h
- Hammerstein system
- Hammerstein–Wiener model
- Hanning pulse
- heart rate variability (HRV)
- Heisenberg’s principle
- Hermitian signal
- Hermitic transpose operator
- heteroscedastic
- Hilbert–Schmidt component analysis (HSCA)
- Hilbert–Schmidt independence criterion (HSIC)
- Hilbert space
- hinge loss
- histogram kernel
- Holter
- homoscedastic
- Hotelling’s test
- Huber
- ɛ‐Huber
- Huber loss
- hyperparameters
- hyperresolution method
- hyperspectral
- hypothesis testing
i
- ill‐posed problem
- incomplete Cholesky decomposition (ICD)
- independent component analysis (ICA)
- indoor location
- information divergence
- information potential
- information‐theoretic learning
- inner product see also dot product; scalar product
- inner product space
- innovation process
- in‐phase and quadrature‐phase
- input features
- input space
- ɛ‐insensitive loss
- interception
- interpolation
- invariance learning
- isomap
j
- Jacobian weighting
- Jensen–Shannon
- jitter
- joint input‐output mapping
k
- Kalman
- Kalman filter
- Karhunen–Loeve
- Karush–Kuhn–Tucker conditions
- kernel
- kernel adaptive filtering
- kernel alignment
- kernel autoregressive and moving average (KARMA)
- kernel blind source separation (KBSS)
- kernel canonical correlation analysis (KCCA)
- kernel density estimation
- kernel dependence estimation
- kernel dimensionality reduction (KDR)
- kernel entropy component analysis (KECA)
- Kernel Fisher’s discriminant analysis (KFDA)
- kernel generalized variance (KGV)
- kernel independent component analysis (KICA)
- kernelization
- kernel least mean squares (KLMS)
- kernel manifold alignment (KEMA)
- kernel matrix
- kernel mean matching (KMM)
- kernel methods
- kernel multivariate analysis (KMVA)
- kernel mutual information (KMI)
- kernel orthonormalized partial least squares (KOPLS)
- kernel partial least squares (KPLS)
- kernel principal component analysis (KPCA)
- kernel recursive least squares (KRLS)
- kernel ridge regression (KRR)
- kernel signal to noise ratio (KSNR)
- kernel trick
- Kirchoff operator
- Kirkwood distribution taking
- k‐means
- k nearest neighbors (k‐NN)
- Kronecker delta
l
- Label Propagation
- Lagrange functional
- Laplace–Beltrami operator
- Laplace–de Rham operator
- Laplacian eigenmaps (LE)
- Laplacian noise
- Laplacian operator
- Large Margin Filtering (LMF)
- large‐scale
- latent space
- least absolute deviation (LAD)
- least absolute shrinkage and selection operator (LASSO)
- least mean squares (LMS)
- least squares (LS)
- Least‐Squares Support Vector Machine (LS‐SVM)
- linear and time‐invariant (LTI) systems
- linear discriminant analysis (LDA)
- linear independence
- l1‐norm
- l2‐norm
- locally linear embedding (LLE)
- logistic regression
- Lomb periodogram
- Lorenz
m
- Mackey–Glass
- magnetic resonance imaging (MRI)
- manifold alignment
- manifolds
- Margenau–Hill distribution
- marketing
- Markov chain
- matched filter
- maximum a posteriori (MAP)
- maximum likelihood (ML)
- maximum mean discrepancy (MMD)
- minimum power distortionless response (MPDR)
- maximum variance unfolding (MVU)
- mean map kernel
- medical imaging
- memory depth
- Mercer, James
- Mercer’s kernel
- Mercer’s theorem
- M‐estimate
- metric
- Mexican hat wavelet
- MIMO see multi‐input multi‐output (MIMO)
- minimax
- minimum mean square error (MMSE)
- minimum noise fraction (MNF)
- minimum phase
- minimum variance distortionless response (MVDR)
- model diagnosis
- modulated kernel
- modulation
- moving average (MA)
- multiclass
- multidimensional sampling
- multidimensional scaling (MDS)
- multidimensional signal
- multi‐input multi‐output (MIMO)
- multilabel
- multi‐output
- multiple kernel learning (MKL)
- multiple signal classification (MUSIC)
- multiresolution analysis
- multispectral remote‐sensing
- multiuser detection
- mutual information
n
- Nadayara–Watson (NW)
- natural signals
- neural networks
- neuron
- noise
- nonlinear algorithms
- nonlinear channel identification
- nonlinearity/nonlinearities
- nonlinear signal model
- nonlinear SVM
- nonlinear system identification
- nonparametric
- nonparametric spectral analysis
- nonuniform interpolation
- nonuniform sampling
- normal equation
- normalization
- null hypothesis
- Nyquist pulse
- Nyquist theorem
o
- one‐against‐one (OAO)
- one‐class classification
- one‐class support measure machines (OC‐SMM)
- one‐class support vector machine
- online learning
- online regression
- online sparsification
- optimization functional
- optimized kernel entropy component analysis (OKECA)
- orthogonal base
- orthogonal frequency division multiplexing (OFDM)
- orthogonality
- orthogonal subspace projection (OSP)
- orthonormal base
- outlier
- overfitting
p
- Page distribution
- parallelization
- parameter estimation
- parametric spectral analysis
- Parseval identity
- Parseval’s theorem
- parsimonious
- Parzen windows
- pervasive change
- phase
- posterior probability
- power
- power spectral density
- pre‐image
- primal‐dual functional
- primal representation
- principal component analysis (PCA)
- prior probability
- probabilistic cluster kernel
- probability density function
- probability product kernel
- projections
- promotion
- pseudoinverse
- pyramid match kernel
- Pytagorean theorem
q
- Q‐mode
- QRS complex
- quadrature amplitude modulation (QAM)
- quadrature‐phase see in‐phase and quadrature‐phase
- quadrature‐phase shift keying (QPSK)
r
- radar
- radial basis function (RBF)
- random Fourier features (RFF)
- rank
- Rayleigh distribution
- received signal strength
- recursive filters
- recursive least squares
- recursivity
- reflectivity
- regression
- regularization
- relevance vector machine (RVM)
- reliability
- remote sensing
- Rényi entropy
- replication (bootstrap)
- representer theorem
- reproducing kernel Hilbert space (RKHS)
- reproducing property
- resample (bootstrap)
- residual
- Riesz representation theorem
- Rihaczek distribution
- RKHS signal model (RSM)
- R‐mode
- running spectrum
s
- sample selection
- sampling
- sampling period
- satellite image
- scalar product see also inner product
- seismology
- self‐organizing map (SOM)
- semiparametric regression (SR)
- semisupervised
- Shannon
- Shannon’s sampling theorem
- shift‐invariant
- signal
- signal detection
- signal interpolation
- signal model
- signal space
- signal‐to‐noise ratio (SNR)
- similarity
- sinc function
- sinc interpolation
- sinc interpolator
- single side‐band
- slack variable
- snapshot
- social networks
- sparse deconvolution
- sparse kernel feature extraction
- sparse learning
- sparsity
- spatial reference
- spectral
- spectral angle mapper (SAM)
- spectrogram
- spectrum
- speech recognition
- stacked kernel
- state‐space representation
- steering vector
- stiffness matrix
- structural risk
- structured output learning
- structure‐preserving algorithms
- subband coding algorithm
- subspace
- subspace detector
- subspace methods
- support vector
- support vector domain description (SVDD)
- support vector machine for digital signal processing (SVM for DSP)
- support vector machines (SVMs)
- support vector regression (SVR)
- surrogate
- synthesis equation
- system identification
- systems with memory
t
- tachogram
- temporal reference
- tensor‐product kernel
- tessellation
- texture classification
- thermal noise
- thin plate spline
- Tikhonov regularization
- time series prediction tin plate spline
- transductive support vector machine (TSVM)
- transfer component analysis (TCA)
- transfer learning
- transform coding
- translation‐invariant kernel
- triangle inequality
- Tutte Laplacian
u
- ultrasound
- unmixing
- unscented Kalman filter (UKF)
- unsupervised
v
- Vapnik‐Chervonenkis capacity (VCC)
- variance
- vector quantization algorithms
- vector space
- Volterra
- Voronoi
w
- warped Gaussian Process Regression (WGP)
- wavelet function
- Welch periodogram
- Wiener
- Wiener filter
- Wiener system
- Wigner–Ville distribution
y
- Yen’s interpolator
z
- z‐transform
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