CDA-9529520 Barreto, Armando B. Yen, Kang Florida International University CISE Research Instrumentation: Multiprocessor Workstation for Advanced Digital Signal Processing Research Emerging Digital Signal Processing techniques are being applied to the solution of challenging problems of signal detection and system modeling: Dynamic neural networks are used as spatio-temporal classifiers for the detection of electroencephalographic (EEG) patterns that can be elicited voluntarily, as part of the process of motion preparation. Reliable detection of these patterns will provide the basis for the development of a new form of computer interface that will be accessible even to individuals deprived of motor execution functions. Similarly, chaotic dynamics analysis is being applied for the detailed study of the three-dimensional propagation of ocean acoustic waves. Indices such as the Lyapunov exponent are numerically estimated using real sound propagation data collected in the North Atlantic to characterize the chaotic properties of the phenomenon. While these emerging DSP techniques hold great promise to increase our capability to obtain useful information from signals and develop accurate models of physical phenomena, they are complex and computationally intensive. The availability of multiprocessor workstations is necessary to shorten the algorithm development and analysis cycles (i.e., large-scale dynamic neural network training, numerical Lyapunov exponent estimation, etc.) to practical levels. Additionally, these systems will familiarize our faculty and students with parallel algorithm development techniques
