Transformer is pivotal in Large Language Models (LLMs), enabling superior performance in language tasks. However, the abundance of parameters poses a challenge for deploying …
As the demands for railway transportation safety increase, traditional methods of rail track inspection no longer meet the needs of modern railway systems. To address the issues of …
In recent years, stock price trend prediction has been a hot topic in the field of AI for finance. Meanwhile, with the constant fluctuations in financial markets, investors …
The processing-in-memory architecture based on memristors has been widely studied for hardware implementation in neural networks, serving as a solution to address the von Neumann …
Predicting stock price trends in High-frequency trading (HFT) demands utmost time sensitivity and resource efficiency. Previous research has stacked attention mechanisms with …
In deep learning, quantization is employed to tackle deployment challenges of neural networks in resource-limited environments like mobile and edge devices. Traditional …
In this paper, a technique for the Berlekamp-Massey(BM) algorithm is provided to reduce the latency of decoding and save decoding power by early termination or early-stopped …
Joint Souce-Channel Code based on QC-LDPC codes on the FPGA platform
We designed a new hardware architecture that uses a non-blocking network for accelerating the convolutional neural network (CNN)
A highly integrated system-on-chip for the on-board unit in the electronic toll collection system is presented.