Sampled-data IIR filtering via time-mode signal processing

Abstract

ACKNOWLEDGMENTSFirst, I would like to thank my supervisor, Professor Gordon Roberts, for giving me the opportunity to study in his research group. I would not have been able to complete this thesis without his guidance, his enthusiasm, and his dedication.He has always been able and available to offer me both professional and academic advice, for which I will always be grateful. To Dong ( -ii - ABSTRACTIn this work, the design of sampled-data infinite impulse response filters based on time-mode signal processing circuits is presented. Time-mode signal processing (TMSP), defined as the processing of sampled analog information using timedifference variables, has become one of the more popular emerging technologies in circuit design. As TMSP is still relatively new, there is still much development needed to extend the technology into a general signal-processing tool. In this work, a set of general building block will be introduced that perform the most basic mathematical operations in the time-mode. By arranging these basic structures, higher-order timemode systems, specifically, time-mode filters, will be realized. Three second-order time-mode filters (low-pass, band-reject, high-pass) are modeled using MATLAB, and simulated in Spectre to verify the design methodology. Finally, a damped integrator and a second-order low-pass time-mode IIR filter are both implemented using discrete components.-iii -

An Approach to Dynamic Sensing Data Fusion

“…According to the current changing degree of collection data, adaptively adjust the acquisition timeintervals, i.e., designate a basic acquisition time unit in advance, and the practical collection timeinterval is K times the basic acquisition time unit (K is an integer).When the collection timeinterval needs to be increased, appropriately increase the value of K; otherwise appropriately decrease the value of K acquisition time. The existing research includes [14,15,16].…”