A Low gate count reconfigurable architecture for biomedical signal processing applications

Abstract

A new reconfigurable architecture for biomedical applications is presented in this paper. The architecture targets frequently encountered functions in biomedical signal processing algorithms thereby replacing multiple dedicated accelerators and reports low gate count. An optimized implementation is achieved by mapping methodologies to functions and limiting the required memory leading directly to an overall minimization of gate count. The proposed architecture has a simple configuration scheme with special provision for handling feedback. The effectiveness of the architecture is demonstrated on an FPGA to show implementation schemes for multiple DSP functions. The architecture has gate count of $$\approx$$ ≈ 25k and an operating frequency of 46.9 MHz.

Deep Conviction Systems for Biomedical Applications Using Intuiting Procedures With Cross Point Approach

“…This is demonstrated at iteration 80, where a high activation function is achieved for 2.5 scaling periods. Because the proportion ratio in the existing model ( 9 ) is not properly defined, the activation period remains at 1 for even two iteration periods. This demonstrates that the projected deep learning model produces the best iteration results with the best activation functions.…”

“…Furthermore, biological signals are integrated at a massive scale utilizing gate count technology ( 9 ), and various signals are handled using system architectures. The operating frequencies of various signals are not determined due to the presence of diverse designs, resulting in a miscount of separate integration gates.…”