Efficient Implementation of Stochastic Computing Based Deep Neural Network on Low Cost Hardware with Saturation Arithmetic
نویسندگان
چکیده
منابع مشابه
Hardware Efficient Implementation of Neural Network
Neural network is being used in many real life applications like prediction, classification etc. In this paper we present an FPGA hardware efficient implementation of neural network where we have implemented a multilayer feed forward network. We have used CORDIC algorithms of HP-35 scientific calculator for this purpose. The CORDIC algorithm is an approximation technique to compute trigonometri...
متن کاملDeepPicar: A Low-cost Deep Neural Network-based Autonomous Car
We present DeepPicar, a low-cost deep neural network (DNN) based autonomous car platform. DeepPicar is a small scale replication of a real self-driving car called Dave2 by NVIDIA, which drove on public roads using a deep convolutional neural network (CNN), that takes images from a front-facing camera as input and produces car steering angles as output. DeepPicar uses the exact same network arch...
متن کاملLow - Power Stochastic Arithmetic Feed - Forward Neural Network
I thank my advisor Yngvar Berg for accepting me as one of his students, and so making this work possible, and for introducing me to the very interesting field of neural computation. I will also thank him for being encouraging, and allowing me a great freedom in choice of methods and solutions. Many thanks to Tor Sverre Lande as well, for his constructive critisism of circuit implementations. Co...
متن کاملEfficient Gestures and Voice Based Computing using Hardware Implementation
This research is focused on solving speed and accuracy problems that current Human-Computer Interface (HCI) fights with. The system uses a separate hardware and multimodal interface to improve system performance and reduce error rate. By using multimodal interface, the gestures and speech both will be used to interact with computers. With the help of hardware circuitry we can improve the speed ...
متن کاملDeep Neural Network based system for solving Arithmetic Word problems
This paper presents DILTON, a system which solves simple arithmetic word problems. DILTON first predicts the operation that is to be performed (’-’,’+’,’*’,’/’) through a deep neural network based model and then uses it to generate the answer. DILTON divides the question into two parts worldstate and query as shown in Figure 1. The worldstate and the query are processed separately in two differ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computer Science
سال: 2020
ISSN: 1549-3636
DOI: 10.3844/jcssp.2020.1570.1584