Prediction of EEG signal from past samples is needed for early diagnosis of patients, suffering from frequent epileptic seizure and/or psychotherapeutic treatment of psychiatric patients. This paper compares the performance of various digital filter algorithms to identify the right candidate for application in EEG prediction. The study includes variation of filter order and past sample size, an...

The traffic signals available in the present are based on the static feed of time without considering the actual available traffic. This leads to a situation where vehicles wait unnecessarily in one of the lanes while the traffic flow is not up to the considerable amount in the other lane. This paper provides a system to monitor the traffic flow automatically in traffic signals where video came...

Title of dissertation: MODEL-BASED GENOMIC/PROTEOMIC SIGNAL PROCESSING IN CANCER DIAGNOSIS AND PREDICTION Peng Qiu Doctor of Philosophy, 2007 Dissertation directed by: Professor K. J. Ray Liu Department of Electrical and Computer Engineering In recent years, high throughput measurement technologies (gene microarray, protein mass spectrum) have made it possible to simultaneously monitor the expr...

The problem of parameter estimation in chaotic noise is considered in this paper. Based on the inherently deterministic nature of a chaotic signal — the short term predictability, a novel estimation approach called minimum nonlinear prediction error (M) technique is proposed. The parameters of a signal can be accurately estimated by minimizing the nonlinear prediction error of the output of an ...

Protein targeting in eukaryotic cells is vital for cell survival and development. N-terminal signal peptides guide proteins to the membrane of the endoplasmic reticulum (ER) and initiate translocation into the ER lumen. Here, we review the status of signal peptide architecture and prediction with an emphasis on exceptionally long signal peptides, which often escape the notion of the currently a...