Unsupervised Signal Processing: Channel Equalization and Source Separation provides a unified and systematic presentation of topics such as blind equalization, source separation, and unsupervised as well as nonlinear adaptive filtering. Extending classical results in literature, this book addresses new issues on static and dynamic convergence of Bussgang algorithsm. It explores emergent trends like neuro-fuzzy systems and evolutionary algorithms. The text pays special attention to the equivalence relations between the ...
Read More
Unsupervised Signal Processing: Channel Equalization and Source Separation provides a unified and systematic presentation of topics such as blind equalization, source separation, and unsupervised as well as nonlinear adaptive filtering. Extending classical results in literature, this book addresses new issues on static and dynamic convergence of Bussgang algorithsm. It explores emergent trends like neuro-fuzzy systems and evolutionary algorithms. The text pays special attention to the equivalence relations between the different unsupervised criteria, including the relationships with Wiener theory. It also includes applications to wireless communications and MIMO systems.
Read Less
