## 留言板

 引用本文: 季渊, 陈文栋, 冉峰, 张金艺, DavidLILJA. 具有二维状态转移结构的随机逻辑及其在神经网络中的应用[J]. 电子与信息学报, 2016, 38(8): 2099-2106.
JI Yuan, CHEN Wendong, RAN Feng, ZHANG Jinyi, David LILJA. Stochastic Logics with Two-dimensional State Transfer Structure and Its Application in the Artificial Neural Network[J]. Journal of Electronics and Information Technology, 2016, 38(8): 2099-2106. doi: 10.11999/JEIT151233
 Citation: JI Yuan, CHEN Wendong, RAN Feng, ZHANG Jinyi, David LILJA. Stochastic Logics with Two-dimensional State Transfer Structure and Its Application in the Artificial Neural Network[J]. Journal of Electronics and Information Technology, 2016, 38(8): 2099-2106.

## Stochastic Logics with Two-dimensional State Transfer Structure and Its Application in the Artificial Neural Network

Funds:

The National Natural Science Foundation of China (61376028)

• 摘要: 随机计算是一种特殊的基于概率数据码流的数学计算方法，其优点在于可以采用非常简单的数字逻辑完成复杂数学运算，从而大幅降低硬件实现成本。该文首先讨论了随机计算的基本原理和主要运算逻辑，论述了传统线性状态机的不足，并分析了一种2维状态转移拓扑结构，推导了通过2维有限状态机实现高斯函数的方法。在此基础上，提出一种随机径向基函数神经网络模型，其硬件实现成本非常低，而性能与传统神经网络相当。两类模式识别实验结果显示，所提出的随机径向基函数神经网络的输出值均方误差与相应结构传统神经网络的差别小于1.3%。FPGA实验结果显示，数据宽度为12位时，随机中间神经元的电路面积仅为传统插值查表结构的1.2%、坐标旋转数字计算方法(CORDIC)的2%。通过改变输入码流长度，该神经网络可以在处理速度、功耗和准确性之间作出平衡，具有应用灵活性，适用于对成本、功耗要求较高的应用如嵌入式、便携式、穿戴式设备。
•  [1] GAINES B R. Stochastic Computing Systems (Chapters) in Advances in Information Systems Science[M]. New York: Plenum, 1969: 37-172. [2] HAYES J P. Introduction to stochastic computing and its challenges[C]. 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, 2015: 1-3. doi:  10.1145/2744769.2747932. [3] ALAGHI A and HAYES J P. Survey of stochastic computing[J]. ACM Transactions on Embedded Computing Systems, 2013, 12(2s): 1-19. doi:  10.1145/2465787.2465794. [4] MOONS B and VERHELST M. Energy-efficiency and accuracy of stochastic computing circuits in emerging technologies[J]. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2014, 4(4): 475-486. doi:  10.1109/JETCAS.2014.2361070. [5] BROWN B D and CARD H C. Stochastic neural computation. I. Computational elements[J]. IEEE Transactions on Computers, 2001, 50(9): 891-905. doi:  10.1109/12.954505. [6] QIAN Weikang, LI Xin, RIEDEL M D, et al. An architecture for fault-tolerant computation with stochastic logic[J]. IEEE Transactions on Computers, 2011, 60(1): 93-105. doi:  10.1109/TC.2010.202. [7] HAN Jie, CHEN Hao, LIANG Jinghang, et al. A stochastic computational approach for accurate and efficient reliability evaluation[J]. IEEE Transactions on Computers, 2014, 63(6): 1336-1350. doi:  10.1109/TC.2012.276. [8] ALAWAD M and LIN Mingjie. FIR filter based on stochastic computing with reconfigurable digital fabric[C]. 2015 IEEE 23rd Annual International Symposium on Field- Programmable Custom Computing Machines (FCCM), Vancouver, BC, Canada, 2015: 92-95. doi: 10.1109/FCCM. 2015.32. [9] TEHRANI S S, NADERI A, KAMENDJE G A, et al. Majority-based tracking forecast Memories for Stochastic LDPC Decoding[J]. IEEE Transactions on Signal Processing, 2010, 58(9): 4883-4896. doi:  10.1109/TSP.2010.2051434. [10] LI Peng, LILJA D J, QIAN Weikang, et al. Computation on stochastic bit streams digital image processing case studies[J]. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2014, 22(3): 449-462. doi: 10.1109/TVLSI.2013. 2247429. [11] ZHANG Da and LI Hui. A stochastic-based FPGA controller for an induction motor drive with integrated neural network algorithms[J]. IEEE Transactions on Industrial Electronics, 2008, 55(2): 551-561. doi:  10.1109/TIE.2007.911946. [12] 王守觉, 李兆洲, 陈向东, 等. 通用神经网络硬件中神经元基本数学模型的讨论[J]. 电子学报, 2001, 29(5): 576-580. [13] WANG Shoujue, LI Zhaozhou, CHEN Xiangdong, et al. Discussion on the basic mathematical models of neurons in general purpose neurocomputer[J]. Acta Electronica Sinica, 2001, 29(5): 576-580. [14] 吴大鹏, 赵莹, 熊余, 等. 基于小波神经网络的告警信息相关性挖掘策略[J]. 电子与信息学报, 2014, 36(10): 2379-2384. doi: 10.3724/SP.J.1146. 2013.01701. [15] WU Dapeng, ZHAO Ying, XIONG Yu, et al. Alarm information relevance mining mechanism based on wavelet neural network[J]. Journal of Electronics Information Technology, 2014, 36(10): 2379-2384. doi: 10.3724/SP.J.1146. 2013.01701. [16] BROWN B D and CARD H C. Stochastic neural computation. II. Soft competitive learning[J]. IEEE Transactions on Computers, 2001, 50(9): 906-920. doi:  10.1109/12.954506. [17] LI Peng, LILJA D J, QIAN W K, et al. The synthesis of complex arithmetic computation on stochastic bit streams using sequential logic[C]. 2012 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), San Jose, CA, USA, 2012: 480-487. doi:  10.1145/2429384.2429483. [18] JI Yuan, RAN Feng, MA Cong, et al. A hardware implementation of a radial basis function neural network using stochastic logic[C]. 2015 Design, Automation Test in Europe Conference Exhibition (DATE), Grenoble, France, 2015: 880-883. [19] 马承光, 仲顺安, LILJA D J, 等. 基于超几何分解的随机运算系统分析方法[J]. 电子与信息学报, 2013, 35(2): 355-360. doi:  10.3724/SP.J.1146.2012.00711. [20] MA Chengguang, ZHONG Shunan, LILJA D J, et al. Analysis method of stochastic computing system based on hypergeometric decomposition[J]. Journal of Electronics Information Technology, 2013, 35(2): 355-360. doi: 10.3724/ SP.J.1146.2012.00711.
•  [1] 徐莹莹, 沈红斌.  基于模式识别的生物医学图像处理研究现状, 电子与信息学报. doi: 10.11999/JEIT190657 [2] 刘斌, 高强.  基于二维不可分小波变换的矩不变量, 电子与信息学报. doi: 10.11999/JEIT151218 [3] 张灿龙, 唐艳平, 李志欣, 马海菲, 蔡冰.  基于二阶空间直方图的双核跟踪, 电子与信息学报. doi: 10.11999/JEIT141321 [4] 汝小虎, 柳征, 姜文利, 黄知涛.  带虚警抑制的基于归一化残差的野值检测方法, 电子与信息学报. doi: 10.11999/JEIT150469 [5] 高发荣, 王佳佳, 席旭刚, 佘青山, 罗志增.  基于粒子群优化-支持向量机方法的下肢肌电信号步态识别, 电子与信息学报. doi: 10.11999/JEIT141083 [6] 钱晓亮, 郭雷, 韩军伟, 胡新韬, 程塨.  视觉显著性检测：一种融合长期和短期特征的信息论算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2012.01251 [7] 孙志军, 薛磊, 许阳明.  基于深度学习的边际Fisher分析特征提取算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2012.00949 [8] 王永茂, 徐正光, 赵珊.  基于自适应近邻图嵌入的局部鉴别投影算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2012.00793 [9] 王进, 丁凌, 孙开伟, 李钟浩.  演化超网络在多类型癌症分子分型中的应用, 电子与信息学报. doi: 10.3724/SP.J.1146.2012.01171 [10] 张启忠, 席旭刚, 罗志增.  基于非线性特征的表面肌电信号模式识别方法, 电子与信息学报. doi: 10.3724/SP.J.1146.2012.01325 [11] 胡正平, 王玲丽.  基于L1范数凸包数据描述的多观测样本分类算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2011.00545 [12] 张洁, 景晓军, 刘馨靖, 李帅.  一种基于模式熵的残缺指纹识别算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2012.00701 [13] 俞璐, 谢钧, 朱磊.  一种基于目标空间的局部判别投影方法, 电子与信息学报. doi: 10.3724/SP.J.1146.2010.00939 [14] 刘忠宝, 王士同.  基于熵理论和核密度估计的最大间隔学习机, 电子与信息学报. doi: 10.3724/SP.J.1146.2010.01434 [15] 张亮, 黄曙光, 郭浩.  快速核有监督局部保留投影算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2010.01044 [16] 郑建炜, 王万良, 姚信威.  基于子块优化及全局整合的局部判别投影法, 电子与信息学报. doi: 10.3724/SP.J.1146.2010.01358 [17] .  一种新的基于距离加权的模板约简K近邻算法, 电子与信息学报. doi: 10.3724/SP.J.1146.2011.00051 [18] 杨丹, 李博, 赵红.  鲁棒视觉词汇本的自适应构造与自然场景分类应用, 电子与信息学报. doi: 10.3724/SP.J.1146.2009.01323 [19] 宋立新, 高凤娇, 郗朝晖.  二维EMD分解方法的比较与改进, 电子与信息学报. doi: 10.3724/SP.J.1146.2007.01871 [20] 杨烜, 裴继红, 张智雄.  图像局部弹性变换中径向基函数紧支撑集的选取, 电子与信息学报. doi: 10.3724/SP.J.1146.2007.00951
• 点击查看大图
##### 计量
• 文章访问数:  609
• HTML全文浏览量:  39
• PDF下载量:  528
• 被引次数: 0
##### 出版历程
• 收稿日期:  2015-11-03
• 修回日期:  2016-04-08
• 刊出日期:  2016-08-19

### 目录

/

• 分享
• 用微信扫码二维码

分享至好友和朋友圈

官方微信，欢迎关注