Lawrence Livermore National Laboratory



Jim Candy Writes New Textbook

Book cover

Described as "a bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems," Model-Based Processing focuses on subspace approaches to system-identification problems, teaching readers to identify models quickly and incorporate them into processing problems, including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that can be adapted to dynamic environments.

Topics include Kalman filtering, practical processor designs, model development and practical applications in model-based signal processing, subspace approach that applies subspace algorithms to synthesized examples and actual applications, and statistical signal processing and subspace identification.

Candy is chief scientist for engineering at LLNL, a distinguished member of the technical staff, and the founder of the Center for Advanced Signal and Image Sciences (CASIS), as well as a UCSB professor and fellow of the IEEE and the Acoustical Society of America.