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1. Positive polynomials. 1.1 Types of polynomials. 1.2 Positive polynomials. 1.3 Toeplitz positivity conditions. 1.4 Positivity on an interval. 1.5 Details and other facts. 1.6 Bibliographical and historical notes.
2. Gram matrix representation. 2.1 Parameterization of trigonometric polynomials. 2.2 Optimization using the trace parameterization. 2.3 Toeplitz quadratic optimization. 2.4 Duality. 2.5 Kalman-Yakubovich-Popov lemma. 2.6 Spectral factorization from a Gram matrix. 2.7 Parameterization of real polynomials. 2.8 Choosing the right basis. 2.9 Interpolation representations. 2.10 Mixed representations. 2.11 Fast algorithms. 2.12 Details and other facts. 2.13 Bibliographical and historical notes.
3. Multivariate polynomials. 3.1 Multivariate polynomials. 3.2 Sum-of-squares multivariate polynomials. 3.3 Sum-of-squares of real polynomials. 3.4 Gram matrices of trigonometric polynomials. 3.5 Sum-of-squares relaxations. 3.6 Gram matrices from partial bases. 3.7 Gram matrices of real multivariate polynomials. 3.8 Pairs of relaxations. 3.9 The Gram pair parameterization. 3.10 Polynomials with matrix coefficients. 3.11 Details and other facts. 3.12 Bibliographical and historical notes.
4. Polynomials positive on domains. 4.1 Real polynomials positive on compact domains. 4.2 Polynomials positive on frequency domains. 4.3 Bounded Real Lemma. 4.4 Positivstellensatz. 4.5 Details and other facts. 4.6 Bibliographical and historical notes.
5. Design of FIR filters. 5.1 Design of FIR filters. 5.2 Design of 2-D FIR filters. 5.3 FIR deconvolution. 5.4 Bibliographical and historical notes.
6. Orthogonal filterbanks. 6.1 Two-channel filterbanks. 6.2 Signal-adapted wavelets. 6.3 GDFT modulated filterbanks. 6.4 Bibliographical and historical notes.
7. Stability. 7.1 Multidimensional stability tests. 7.2 Robust stability. 7.3 Convex stability domains. 7.4 Bibliographical and historical notes.
8. Design of IIR filters. 8.1 Magnitude design of IIR filters. 8.2 Approximate linear-phase designs. 8.3 2D IIR filter design. 8.4 Bibliographical and historical notes
Appendix A: semidefinite programming. Appendix B: spectral factorization.
References.
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Add Positive Trigonometric Polynomials and Signal Processing Applications, This book gathers the main recent results on positive trigonometric polynomials within a unitary framework. The book has two parts: theory and applications. The theory of sum-of-squares trigonometric polynomials is presented unitarily based on the concept, Positive Trigonometric Polynomials and Signal Processing Applications to the inventory that you are selling on WonderClubX
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Add Positive Trigonometric Polynomials and Signal Processing Applications, This book gathers the main recent results on positive trigonometric polynomials within a unitary framework. The book has two parts: theory and applications. The theory of sum-of-squares trigonometric polynomials is presented unitarily based on the concept, Positive Trigonometric Polynomials and Signal Processing Applications to your collection on WonderClub |