Preface -- Acknowledgments -- Background and preview -- Stochastic processes and models -- Wiener filters -- Linear prediction -- Method of steepest descent -- Method of stochastic gradient descent -- The least-mean-square (LMS) algorithm -- Normalized least-mean-square (LMS) algorithm and its generalization -- Block-adaptive filters -- Method of least-squares -- The recursive least-square (RLS) algorithm -- Robustness -- Finite-precision effects -- Adaptation in nonstationary environments -- Kalman filters -- Square-root adaptive filtering algorithms -- Order-recursive adaptive filtering algorithm -- Blind deconvention -- Epilogue -- Appendix A: Theory of complex variables -- Appendix B: Wirtinger calculus for computing complex gradients -- Appendix C: Method of Lagrange multipliers -- Appendix D: Estimation theory -- Appendix E: Eigenanalysis -- Appendix F: Langevin equation of nonequilibrium thermodynamics -- Appendix G: Rotations and reflections -- Appendix H: Complex Wishart distribution