This chapter concludes our analysis of neural network models with an overview of some hardware implementations proposed in recent years. In the first chapter we discussed how biological organisms process information. We are now interested in finding out how best to process information using electronic ...
Recently, this wave has spread to the design of neural network accelerators for gaining extremely high performance. However, the amount of related works is incredibly huge and the reported approaches are quite divergent. This research chaos motivates us to provide a comprehensive survey on the ...
- 《Neural Networks the Official Journal of the International Neural Network Society》 被引量: 26发表: 2015年 Design and validation of a real-time spiking-neural-network decoder for brain–machine interfaces Cortically-controlled motor prostheses aim to restore functions lost to neurological disease ...
Bahadır Utku Kesgin and Uğur Teğin propose using a Lorenz attractor as a nonlinear transfer function for neural network nodes. They design a power-efficient electrical circuit and use them for regression and classification test tasks. Bahadır Utku Kesgin Uğur Teğin ArticleOpen Acce...
目测和发在ISCA2016的论文EIE: Efficient Inference Engine on Compressed Deep Neural Network内容一致,补了一些图。是一个神经网络加速器,用硬件加速训练好的网络模型。 6.1 Introduction 为了评估EIE性能,为其建立了行为级描述和RTL级模型,并对RTL模型进行了综合和布局布线,以获得精确的功耗与时钟频率。在9个DNN ben...
To circumvent the von Neumann bottleneck, substantial progress has been made towards in-memory computing with synaptic devices. However, compact nanodevices implementing non-linear activation functions are required for efficient full-hardware implementation of deep neural networks. Here, we present an energ...
NIOS Ⅱ multi-core technology is used to implement the hardware of Hopfield neural network.The method uses interrupt and SDRAM to realize the communication between NIOS Ⅱ multi-cores.Then,the implemented Hopfield network is used for digital number identification.The effectiveness and feasibility of ...
The digital hardware realization of a recurrent neural network for solving the assignment problem is presented. The design is based on an analog neural network and is mapped to a one-dimensional systolic array for parallel processing. The processing elements are connected with a ring topology that ...
Fig. 1: Neural prostheses for sensory feedback restoration. The main building blocks of a neural prosthesis for the somatosensory system are the sensing block, the computing block, and the stimulating block. Sensing technology (e.g., wearable tactile sensors) has to be embedded in the robotic ...
For instance, ref. [4] shows a convolutional neural network (CNN) that uses the Tanh AF in each layer, and ref. [22] presents a neuroevolution of augmenting topology, which employs the Tanh and Gaussian AFs in the hidden layer and output layer, respectively. On the other hand, the expon...