In this paper, we investigate the application of compressive sensing and waveform design for estimating linear time-varying system characteristics. Based on the fact that the spre...
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Neural Systems Engineering Lab (NSEL) at Michigan State University focuses on advancing neuroinformatics science by engineering new theoretical, computational and experimental tool...
A new method is introduced that makes use of sparse image representations to search for approximate nearest neighbors (ANN) under the normalized inner-product distance. The approa...
We develop a new receiver for orthogonal frequency division multiplexing (OFDM) systems in time-varying channels by embedding channel estimation in a low-complexity block turbo eq...