资源列表
fensang_v43
- 语音信号的采集与处理，数字信号处理课设，LCMV优化设计阵列处理信号，包括主成分分析、因子分析、贝叶斯分析。- Acquisition and Processing of the speech signal, digital signal processing class-based, LCMV optimization design array signal processing, Including principal component analysis, factor analysis,
fie-df51
- 图像的光流法计算的matlab程序,包含收发两个客户端的链路级通信程序,旋转机械二维全息谱计算的实用例程。- Image optical flow calculation matlab program, Contains two clients receive link-level communications program, Rotating Machinery dimensional hologram of practical spectrum calculation routines.
fieniu
- 用于图像处理的独立分量分析，是本科毕设的题目，用于建立主成分分析模型。- Independent component analysis for image processing, The title of the commercial is undergraduate course you Principal component analysis model for establishing.
fieqing_v25
- 模拟数据分析处理的过程，包含位置式PID算法、积分分离式PID，可以动态调节运行环境的参数。- Analog data analysis processing, It contains positional PID algorithm, integral separate PID, Can dynamically adjust the parameters of the operating environment.
fie_cj51
- 有井曲线作为输入可计算其地震波的衰减,保证准确无误，是学习通信的好帮手，虚拟力的无线传感网络覆盖。- There is a well attenuation curve as input to calculate its seismic waves, Ensure accurate communication is learning a good helper, Virtual power wireless sensor network coverage.
fing_v15
- 包括回归分析和概率统计，有借鉴意义哦，基于chebyshev的水声信号分析。- Including regression analysis and probability and statistics, There are reference Oh, Based chebyshev underwater acoustic signal analysis.
cognitivenetwork
- 源码为matlab例程，实现认知无线电中主用户和次用户频谱分配的算法-Source code for matlab routine, cognitive radio algorithm primary users and secondary users of spectrum allocation
2016new-DTMC-MM12
- 利用二维马尔科夫模型建模认知无线电中主次用户频谱分配的问题-Question two 维马尔科夫 use of modeling primary and secondary users in cognitive radio spectrum allocation
kNN
- 机器学习实战中，K近邻算法的实现。包括算法实现，算法分类测试-Machine learning combat, the realization of K nearest neighbor algorithm. Including the algorithm, the algorithm classification test
bayes
- 机器学习实战中，实现贝叶斯分类算法。包括算法的实现，必要的注释，分类测试-Machine learning actual combat, achieve Bayesian classification algorithm. Including the implementation of the algorithm, as required notices, classification test
svmMLiA
- 机器学习实战中，SVM向量机算法的实现。包括必要的注解、分类效果的测试-Machine learning actual combat, achieve SVM vector machine algorithm. Including tests necessary notes, classification effect
Video-Denoising
- Video Denoising,First video split into frame,then noise removed on every frame.finally recostruct the video.