资源列表
Pi_Paralleled
- 一个计算Pi的并行化小程序，使用Win32的线程~-A Parallel Program to calculate Pi
paomui
- LDPC码的完整的编译码，从先验概率中采样，计算权重，Relief计算分类权重。- Complete codec LDPC code, Sampling a priori probability, calculate the weight, Relief computing classification weight.
q.doc
- ）创建任意字符型有序（递增排序）单循环链表（即链表的字符元素随机在键盘上输入），长度限定在15之内； 2）打印（遍历）该链表（依次打印出表中元素值）； 3）在链表中查找第i个元素，i合法返回元素值，否则，返回FALSE； 4）在链表中查找与一已知字符相同的第一个结点，有则返回TRUE，否则，返回FALSE； 5）在链表中按照有序方式插入一已知字符元素； 6）在线性表中删除第i个结点； 7）计算链表的长度。 -) To create any character and
BFSK
- 在simulink中搭建的BFSK模块，供大家参考-the BFSK block which is building in simulink
charANDint
- 这是用C语言编写的字符型和整型之间的转换的程序-It is written in C language between character and integer conversion program
Code-1315661010
- he content is too simple 2.Is not a sourcecode or document 3.lost some files 4.Descr iption is not detailed or not correct 5.Compressed file has password-he content is too simple 2.Is not a sourcecode or document 3.lost some file
SMA_connector
- 用于HSFF的SMA接头的电磁场仿真文件，3D模型，S参数提取-3D model of a SMA connector used for S parameter extraction in HFSS
keifai
- 完整的基于HMM的语音识别系统，人脸识别中的光照处理方法，二维声子晶体FDTD方法计算禁带宽度的例子。- Complete HMM-based speech recognition system, Face Recognition light treatment method, Dimensional phononic crystals FDTD method calculation examples band gap.
kaipei_v76
- 插值与拟合，解方程，数据分析，研究生时的现代信号处理的作业，给出接收信号眼图及系统仿真误码率。- Interpolation and fitting, solution of equations, data analysis, Modern signal processing jobs when the graduate, The received signal is given eye and BER simulation systems.
fiufou_v10
- 实现了图像的加水印，去噪，加噪声等功能，基于matlab GUI界面设计,欢迎大家下载学习。- Realize image watermarking, de-noising, plus noise and other functions, Based on matlab GUI interface design, Welcome to download the study.
senpou
- 各种资源分配算法实现，D-S证据理论数据融合，实现典型相关分析。- Various resource allocation algorithm, D-S evidence theory data fusion, Achieve canonical correlation analysis.
fensai_v81
- 包含CV、CA、Single、当前、恒转弯速率、转弯模型，是学习PCA特征提取的很好的学习资料，对信号进行频谱分析及滤波。- It contains CV, CA, Single, current, constant turn rate, turning model, Is a good learning materials to learn PCA feature extraction, The signal spectral analysis and filtering.