happysheep2008的专栏

模型压缩、硬件加速、NAS相关文献

Ultra96v2快速指南，中文翻译，实测有效。文中介绍了如何连接板子，上电，连接终端，如何连接wifi，断电等等一系列的操作。解决了无法连接WiFi的问题。

该程序所使用的数据集是来自麻省理工大学的mit-bih-arrhythmia-database标准心电数据集，通过文件1读取该数据集数据到MATLAB中，然后对该信号做预处理，使用的方法包括小波去噪、低通滤波、高通滤波，去除基线漂移、工频噪声、肌肉收缩等低频和高频噪声

本程序代码详细展示了如何用matlab读取图像文件，并对其进行简单处理，包括计算直方图，直方图均衡，平移，旋转，高斯滤波、平均滤波、中值滤波等

Abstract—In this letter, measured adjacent channel leakage ratio (ACLR) results using a GaN Doherty power amplifier will show that for less than 2000 coefficients, sigmoid activated deep neural network (DNN)-based digital predistorter (DPD) outperforms rectified linear unit (ReLU) activation by up to 2 dB even when the number of layers of the network is increased. When the number of coefficients exceeds 2000 ReLU outperforms sigmoid activation with an improvement of up to 3–4 dB in ACLR suppression. Furthermore, to achieve an ACLR level of −54 dBc or better, the number of coefficients required to implement the DNN-DPD can be reduced by a factor of 150 when using ReLU rather than sigmoid activation.

Learn from others. One thing that never ceases to amaze me is the fact that many submissions are prepared as if the writer had never read a good scientific paper, even though 50 may be cited! One sometimes wonders whether the author has ever read any of them carefully. As with many things in life, we can learn most from the experience of others and/or trying to do it ourselves, rather than from textbooks. You learn to write papers by reading other peoples’ papers, and by writing them yourself. I hope that Editorials such as this may help, but learning by doing is what is really important.

I am convinced that the Experimental section of almost all papers could be significantly shortened. It should concentrate on providing the information that the reader really needs to have in order to be satisfied on the above two points, and pro- vide a list of equipment used in the Supplementary Material section. Surely that is enough!

Perhaps I could ask those who read this editorial a rhe- torical question. When did you last fully read the Introduc- tion to a scientific paper in which you were interested? I suspect the answer would be ‘‘months ago’’ for most of you. In my experience people first read the Abstract, then the Conclusions, and if there is something of real interest they ‘‘dig into’’ the Results and Discussion sections. Many journals print what are considered the less important sec- tions of a paper, and the References, in a smaller font. Per- haps it is the Introduction that most often deserves this treatment?

随着大数据时代的来临,深度学习技术在从海量数据中提取有价值信息方面发挥着重要作用,已被广泛应用于计算机视觉、语音识别及自然语言处理等领域。本文从深度学习算法的特点和发展趋势出发,分析 FPGA 加速深度学习的优势以及技术挑战;其次,从 SoC FPGA 和标准 FPGA 两个方面介绍了 CPU-FPGA 平台,主要对比分析了两种模型在 CPU 和FPGA 之间数据交互上的区别;接下来,在介绍 FPGA 加速深度学习算法的开发环境基础上,重点从硬件结构、设计思路和优化策略这三个方面详细综述了采用 FPGA 加速卷积神经网络的设计方案;最后展望了 FPGA 加速深度学习算法相关研究工作的发展。

本课题旨在提出一种基于USB2.0和DDR SDRAM的海量数据采集系统的FPGA解决方案，并详细阐述了系统方案设计思路及应用实施方法。该方案根据实际需求，可应用于多种标准下的广播电视信号接收前端，携带方便，功耗低，适用于信号数据的现场采集和存储。

本次设计是基于Altera公司生产的DE0开发板。利用verilog语言实现了AM调制，发射频率为1MHZ。用小三芯和SMA做一根射频线，一端连接电脑音频输出，另一端连接ADDA板输入，用天线连接ADDA板的输出口，在电脑上播放音乐，用一般的AM广播即可接收到音乐信号。

New Users of This Toolbox You can use this toolbox to: •Design filters using advanced design methods •Convert filters to and from coupled-allpass forms •Convert filters to second-order section form •Quantize filters and filter data •Quantize data •Compute quantized FFTs and IFFTs

DE2 Development and Education Board User Manual DE2开发板用户说明书

2008-10-18日重庆移动成都地区笔试题 1 2008年10月16日北京移动在线测试题 5 yybear整理 重庆移动的资料 52 正德厚生，臻于至善 52 笔试规则 52 面试规则 52 招聘方向及岗位： 55 招聘地点及数量（309人，去年360人） 55 职业发展 56 中国移动通信集团公司 （China Mobile Communications Corporation CMCC ） 58 中国移动通信集团重庆有限公司（简称“中国移动重庆公司”） 69 中国移动笔试题集 71 应聘指南 75 百度08-9-24成都电子科技大学笔试题 81 腾讯08-10-11聘（成都重庆地区）笔试题 85 中兴-软件研发2008-10-28成都笔试题 89

还有几盏亮灯？ "大厅里有100盏灯，每盏灯都编了号码，分别为1-100。每盏灯由一个开关来控制。（开关按一下，灯亮，再按一下灯灭。开关的编号与被控制的灯相同。）开始时，灯是全灭的。现在按照以下规则按动开关。 第一次，将所有的灯点亮。 第二次，将所有2的倍数的开关按一下。 第三次，将所有3的倍数的开关按一下。 以此类推。第N次，将所有N的倍数的开关按一下。 问第100次按完以后，大厅里还有几盏灯是亮的。"