资源列表
报表源码sql查询以及导出到EXCEL
- 查询数据库sql数据，并导出至excel模板(Query the database SQL data and export to the excel template)
上位机和下位机串行通信设计
- C#上位机和下位机串行接口通信设计说明帮助文档(The design of serial communication between host computer and slave computer)
上位机与下位机之间通信协议格式
- 上位机与下位机之间穿行接口通信协议格式说明(The interface between the host computer and the lower computer is communicated with the protocol format)
MultiImageViewer
- 多张图片浏览器，放大缩小，鼠标定点缩放，平滑缩放，旋转等。(Multiple photo browsers, zoom in, rotate, etc.)
OpenPCS_Update_656
- OpenPCS_Update_656 升级文件(OpenPCS_Update_656 update files)
C#中串口组件的使用方法总结及上位机制作方法
- C#中串口组件的使用方法总结及上位机制作方法(C# serial components in the use of methods and summary of PC production methods)
sreenivas2009-icassp
- Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of
SPItest.X
- 新手学习用，常见的SPI通讯实例，其中的读和写数据都是随意写的只需要看功能就好。(Novice learning to use, a common example of SPI communication.)
SPL-MaxLP-IEEE Letter2016
- Linear prediction (LP) is an ubiquitous analysis method in speech processing. Various studies have focused on sparse LP algorithms by introducing sparsity constraints into the LP framework. Sparse LP has been shown to be effective in several issu
SR04
- 采用IO触发测距，给至少10us的高电平信号； 模块自动发送8个40KHz的方波，自动检测是否有信号返回； 有信号返回，通过IO输出一高电平，高电平持续的时间就是超声波从发射到返回的时间．距离=(高电平时间*声速(340m/s))/2;(IO triggered ranging is used to give at least 10us of the high level signal; The module automatically sends 8 40KHz Fang Bo, aut
speech reconstruction+SLP
- This paper proposes a new variant of the least square autoregressive (LSAR) method for speech reconstruction, which can estimate via least squares a segment of missing samples by applying the linear prediction (LP) model of speech. First, we show t
speech coding based on SLP-2009
- This paper describes a novel speech coding concept created by introducing sparsity constraints in a linear prediction scheme both on the residual and on the prediction vector. The residual is efficiently encoded using well known multi-pulse excitat