The capabilities of current quantum computers are limited by their high error rates. Thus,
reducing the impact of these errors is one of the crucial challenges for the successful …

Vector similarity search (VSS) for unstructured vectors generated via machine learning
methods is a promising solution for many applications, such as face search. With increasing …

The soft decision decoding algorithm for cyclic codes, especially the maximum likelihood
(ML) decoding algorithm, can obtain significant performance superior to that of algebraic …

Finite State Machine (FSM) is widely used in electronic systems and its reliability is critical to
the system. Ionizing radiation induced soft error is one of the major concerns in the design of …

The size reduction of transistors in the latest flash memory generation has resulted in
programming and data erasure issues within these designs. Consequently, ensuring …

MBU is an increasing challenge in SRAM memory, due to the chip's large area of SRAM,
and supply power scaling applied to reduce static consumption. Powerful ECCs can cope …

This paper proposes a novel iterative decoding method-Gradient Descent Symbol Update-
for real number parity based error correction codes, as well as its corresponding hardware …

With the integration scale level reached in CMOS technology, memory systems provide a
great storage capacity, but at the price of an augment in their fault rate. In this way, the …

Deploying convolutional neural networks (CNNs) in image classification systems requires
balancing conflicting goals, like throughput, power consumption, and silicon area. In safety …

The continuous raise in the integration scale of CMOS technology has provoked an augment
in the fault rate. Particularly, computer memory is affected by Single Cell Upsets (SCU) and …