The extraordinary advances in digital signal processing and digital communications, and the widespread application of sampled signals have created a heavy demand for economical, fast, precise, and efficient digital filters. Consequently, the analysis, design, and implementation of digital filters have received and continue to receive considerable attention by the research community. This fantastic growth, has led to the growth of numerous journals like
and many others. As technology advances and digital hardware becomes more and more sophisticated, new problems are identified and for the many seemingly intractable problems of the past, solutions are beginning to emerge.
Andreas Antoniou and his group are engaged in a fairly broad spectrum of research activities that encompass the analysis, design, and implementation of digital filters. Ongoing research projects include computationally efficient methods for the design of 1-D and 2-D digital filters and equalizers, their VLSI implementation, and the development of digital signal processors and modules of various types. Attention is also paid to the development of new and efficient algorithms for adaptive filters and equalizers. The design methodologies and algorithms under development are regularly based on optimization methods such as quasi-Newton, minimax, and Remez methods and sometimes use neural networks. Particular emphasis is placed on applications related to communications, bathymetry, image processing, multirate processing, and the efficient monitoring of fisheries and the environment.