Delay Lines Using Self-Adapting Time Constants

Shao-Jen Lim and John G. Harris Computational Neuro-Engineering Laboratory University of Florida Gainesville, FL 32611 Abstract| Transversal lters using ideal tap delay lines are a popular form of short-term memory based ltering in adaptive systems. Some applications where these lters have attained considerable success include system identi cation, linear prediction, channel equalization and echo cancellation [1]. The gamma lter improves on the simple FIR delay line by allowing the system to choose a single optimal time-constant by minimizing the Mean Squared Error of the system [8]. However, in practice it is di cult to determine the optimal value of the time constant since the performance surface is nonconvex. Also, many times a single time constant is not su cient to well represent the input signal. We propose a nonlinear delay line where each stage of the delay line adapts its time constant so that the average power at the output of the stage is a constant fraction of the power at the input to the stage. Since this adaptation is independent of the Mean Square Error, there are no problems with local minima in the search space. Furthermore, since each stage adapts its own time constant, the delay line is able to represent signals that contain a wide variety of time scales. We discuss both discreteand continuous-time realizations of this method. Finally, we are developing analog VLSI hardware to implement these nonlinear delay lines. Such an implementation will provide fast, inexpensive, and low-power solutions for many adaptive signal processing applications.