Cover; Copyright Page; Contents; Contributors; Preface; Future Contributions; Chapter 1. V-Vector Algebra and Volterra Filters; I. Introduction; II. Volterra Series Expansions and Volterra Filters; III. V-Vector Algebra; IV. V-Vectors for Volterra and Linear Multichannel Filters; V. A Novel Givens Rotation-Based Fast QR-RLS Algorithm; VI. Nonlinear Prediction and Coding of Speech and Audio by Using V-Vector Algebra and Volterra Filters; VII. Summary; Appendix I: The Givens Rotations; Appendix II: Some Efficient Factorization Algorithms; References

Chapter 2. A Brief Walk through Sampling TheoryI. Starting Point; II. Orthogonal Sampling Formulas; III. Classical Paley-Wiener Spaces Revisited; IV. Sampling Stationary Stochastic Processes; V. At the End of the Walk; References; Chapter 3. Kriging Filters for Space-Time Interpolation; I. Introduction; II. Data Model; III. Review of Kriging Methods; IV. Best Linear Unbiased Prediction; V. Cokriging Filters; VI. Space-Time Kriging Filters; VII. Applications; VIII. Discussion and Conclusion; Appendix: Optimality of Filtering Algorithms; References

Chapter 4.Constructions of Orthogonal and Biorthogonal Scaling Functions and Multiwavelets Using Fractal Interpolation SurfacesI. Introduction; II. Scaling Function Constructions; III. Associated Multiwavelets; IV. Wavelet Constructions; V. Applications to Digitized Images; Appendix; References; Chapter 5. Diffraction Tomography for Turbid Media; I. Introduction; II. Background; III. Diffraction Tomography for Turbid Media: The Forward Model; IV. Backpropagation in Turbid Media.; V. Signal-to-Noise Ratios; VI. Concluding Remarks; References; Chapter 6. Tree-Adapted Wavelet Shrinkage

I. IntroductionII. Comparison of Taws and Wiener Filtering; III. Wavelet Analysis; IV. Fundamentals of Wavelet-Based Denoising; V. Tree-Adapted Wavelet Shrinkage; VI. Comparison of Taws with Other Techniques; VII. Conclusion; References; Index