Abstract
The discipline of signal processing provides formal, mathematical techniques for processing information. The applications of signal processing are countless and make up an increasing amount of all computing performed across all computing platforms. Problems and opportunities are arising, however, that will be met as we learn more about how neurological systems process information. The first problem stems from the evolution of computing devices. For a variety of reasons, high performance computing platforms must employ increasing parallelism to achieve performance improvements. The problem comes from the difficulty in effectively using highly parallel systems. The second problem comes from the need to decrease the power consumption of computing systems. This is true for everything from large systems, where power determines density and cooling costs, to small systems where battery life is the limiting factor. A third problem is inherent in the difficult, ongoing task of making machines intelligent. All of these problems may be addressed by applying techniques learned through the study of neurological systems. These systems are highly parallel and operate very efficiently. Additionally, the intelligence of biological systems is largely due to the ability of these systems to recognize patterns–an ability that greatly exceeds that of synthetic systems in robustness and flexibility. This talk will discuss the problems mentioned above as well as summarizing some recent applications of signal processing that have benefited from the inspiration or modeling of neurological systems.

Biography
David V. Anderson received the B.S and M.S. degrees from Brigham Young University, Provo, UT and the Ph.D. degree from Georgia Institute of Technology Georgia Tech Atlanta, GA, in 1993, 1994, and 1999, respectively. He is an associate professor in the School of Electrical and Computer Engineering at Georgia Tech and an associate director of the Center for Research in Embedded Systems Technology. His research interests include audio and psycho-acoustics, signal processing in the context of human auditory characteristics, and the real-time application of such techniques using both analog and digital hardware. His research has included the development of a digital hearing aid algorithm that has now been made into a successful commercial product. Dr. Anderson was awarded the National Science Foundation CAREER Award for excellence as a young educator and researcher in 2004 and is a recipient of the 2004 Presidential Early Career Awards for Scientists and Engineers PECASE. He has over 60 technical publications and 5 patents/patents pending. Dr. Anderson is a member of the IEEE, the Acoustical Society of America, ASEE, and Tau Beta Pi. He has been actively involved in the development and promotion of computer enhanced education and other education programs.