Numerous real-life systems exhibit complex nonlinear input-output relationships. Kernel
adaptive filters, a popular class of nonlinear adaptive filters, can efficiently model these …

In this article, we propose a multiplierless piecewise linear (PWL) approximation
computation (ML-PLAC) method for nonlinear unary functions. ML-PLAC seeks the minimum …

This paper presents a new A-weighting filter's design and explores the potential of using
approximate multiplication for low-power digital A-weighting filter implementation. It presents …

Digital FIR filters can be efficiently implemented using distributed arithmetic (DA). Original
DA provides low throughput. Parallel DA is proven to be a promising technique for efficient …

Distributed arithmetic (DA) is generally used for area-time efficient implementation of inner
products, where one of the vectors is fixed and known a priori. Therefore, the conventional …

An effective approximate distributed arithmetic (DA) architecture is proposed for adaptive
finite impulse response (FIR) filters. The approximate DA architecture is combined with …

Approximate computing (AC) provides an efficient solution for reducing power, area, and
complexity of digital systems. When backed with distributed arithmetic (DA), AC leverages …

New consumer devices heavily rely on accessible digital signal processors. Every DSP Core
now includes a Multiply and Accumulate unit (MAC), which serves as a key building element …

Convolutional neural network (CNN) is one of the most dominant deep learning networks
with good generalization ability. Its high performance in solving large and complex learning …

At present, product family design has become an important link in enterprise development
and manufacturing. Optimization ideas and technologies are important foundations and core …