Design and implementation of DA FIR filter for bio-inspired computing architecture

Abstract

This paper elucidates the system construct of DA-FIR filter optimized for design of distributed arithmetic (DA) finite impulse response (FIR) filter and is based on architecture with tightly coupled co-processor based data processing units. With a series of look-up-table (LUT) accesses in order to emulate multiply and accumulate operations the constructed DA based FIR filter is implemented on FPGA. The very high speed integrated circuit hardware description language (VHDL) is used implement the proposed filter and the design is verified using simulation. This paper discusses two optimization algorithms and resulting optimizations are incorporated into LUT layer and architecture extractions. The proposed method offers an optimized design in the form of offers average miminimizations of the number of LUT, reduction in populated slices and gate minimization for DA-finite impulse response filter. This research paves a direction towards development of bio inspired computing architectures developed without logically intensive operations, obtaining the desired specifications with respect to performance, timing, and reliability.

Deep learning-based switchable network for in-loop filtering in high efficiency video coding

“…By modelling the deep CNN adaptive filter with 64 kernels and with a weight initializing and weight adjusting network for the frames I, P, and B. But considering the characteristics of P and B frame as it has the information of the previous frame and next frame, the chance of enhancement [18], [19] can be doubled and can cause the worst effect in the visual quality [20] of the output, considering this the frame B is not fit for the deep CNN adaptive filter, instead it can be sent directly through the existing in loop filter [21] in HEVC. Here a pipeline model is designed to solve this issue.…”

Adaptive FIR Filter Design with Approximate Adder and Hybridized Multiplier for Efficient Noise Eradication in Sensor Nodes

“…1 The DSP application noise removal and echo cancelation of WSN based iot signals are the one of the main problems. To solve this problem, FIR [2][3][4][5] based adaptive filters are applied. Where adaptive approaches are needed, adaptive filters are used.…”