Artificial Neural Network Implementation in FPGA Using Multiplexer-Based Weight Updating for Efficient Resource UtilizationRavi KumarDeepak Gupta
The use of artificial intelligence in healthcare applications offers significant accuracy and utility for medical practitioners and patients. Deep learning has made a substantial positive impact on the healthcare industry by reducing the use of medical resources and workloads. Neural networks (NNs), ins...
This paper presents a hardware implementation of multilayer feedforward neural networks (NN) using reconfigurable field-programmable gate arrays (FPGAs). Despite improvements in FPGA densities, the numerous multipliers in an NN limit the size of the network that can be implemented using a single FPGA...
In this paper we present a hardware implementation of Long-Short Term Memory (LSTM) recurrent network on the programmable logic Zynq 7020 FPGA from Xilinx. We implemented a RNN with 2 layers and 128 hidden units in hardware and it has been tested using a character level language model. The ...
select article An Optimized Multi-layer Spiking Neural Network implementation in FPGA Without Multipliers Research articleOpen access An Optimized Multi-layer Spiking Neural Network implementation in FPGA Without Multipliers Ali Mehrabi, Yeshwanth Bethi, André van Schaik, Saeed Afshar ...
implementation because an FPGA implementation offers the flexibility of simple software (re-)configuration in comparison to other digital ASICs. In this paper a hippocampus-inspired spiking neural network is implemented on an FPGA, in order to take advantage of these two characteristics as well as ...
Therefore, the implementation of CNN-based target detection algorithm accelerator using FPGA has become a hot research topic. For example, in 2016, Chen et al. designed a SIMD convolutional neural network acceleration system based on FPGA, which reduced the gap between the theoretical and actual ...
2020OFC论文阅读 T4D.2 FPGA Implementation of Deep Neural Network Based Equalizers for High-Speed PON,程序员大本营,技术文章内容聚合第一站。
In this work, Convolutional Neural Network (CNN) is applied for defect identification of Swiven Cap (one type of medical component) based on Field-Programmable Gate Array (FPGA) implementation. Caffe is used as the platform to develop the CNN model. After training phase, a confusion matrix is...
FPGA Implementation of the Locally Recurrent Probabilistic Neural NetworkThis study is part of the Instituto Nacional de Ciência e Tecnologia em reas midas (INAU / CNPq / UFMT), Cuiaba, Mato Grosso, Research Program on the Pantanal wetlands. The main goal of this proj…" [more]...