Channel coding may be viewed as the best-informed and most potent component of cellular
communication systems, which is used for correcting the transmission errors inflicted by …

General matrix multiplication (GEMM) is universal in various applications, such as signal
processing, machine learning, and computer vision. Conventional GEMM hardware …

General matrix multiply (GEMM) is an important operation in broad applications, especially
the thriving deep neural networks. To achieve low power consumption for GEMM …

Brain computer interfaces (BCIs) have been widely adopted to enhance human perception
via brain signals with abundant spatial-temporal dynamics, such as electroencephalogram …

Stochastic Computing (SC) is designed to minimize hardware area and power consumption
compared to traditional binary-encoded computation, stemming from the bit-serial data …

The ultra-low hardware consumption feature of stochastic decoding has made it a potential
candidate for the implementation of low-density parity-check (LDPC) decoders. However …

Channel coding is a vital but complex component of cellular communication systems, which
is used for correcting the communication errors that are caused by noise, interference and …

This paper presents a high-throughput, energy-efficient, and scalable low-density parity-
check (LDPC) decoder with time-domain (TD) signal processing. The proposed arbiter …

Hybrid low-density parity-check (LDPC) decoding combines conventional Belief-
Propagation (BP) algorithm with stochastic decoding to achieve high performance and low …

This paper presents an efficient combined bit-flipping (BF) and stochastic low-density parity-
check decoder, where a BF decoder is used to achieve a reduction in decoding cycles. A …