搜索资源列表
pcm
- 语音编码方案的选取对移动通信系统的通话质量、信道容量等有重要影响。本文讨论了TD-SCDMA系统中AMR语音编码的自适应机制，同时分析了AMR中代数码本线性预测(ACELP)算法及实现过程。该方案可以在一块TMS320C5510上实现。-The selection of voice coding schemes for mobile communication systems the quality of the call, such as channel capacity have had a
2
- 无线设备综合测试方法，理论测试.测试质量分析，问题定位并进行跟踪、验证 -Comprehensive testing of wireless devices, theory test. Test quality analysis, positioning and tracking problems, verification
Base-band-
- 基带数字传输系统的仿真 基带传输系统的基本结构带限信道的仿真以及性能分析；眼图和星座图判断信号的传输质量。 -Base-band digital transmission system simulation-based transmission system with the basic structure of band-limited channel simulation and performance analysis eye diagrams and constellation t
RLSVLMS
- MMSE忙多用户检测算法的收敛性能分析，通过仿真选取了遗忘因子和训练序列,仿真结果表明该算法具有较小的误码率性能,可以有效地提高通信质量。-MMSE busy multi-user detection algorithm convergence performance analysis, simulation and training forgetting factor selected sequence, the simulation results show that the algorit
xieyi
- 四川维博电能分析模块通信协议，用于市电，电能质量分析-The four Chuan Weibo energy analysis module communication protocol for the mains, power quality analysis
CS-of-multi-static-SAR
- 压缩感知在多基地合成孔径雷达中的应用，关于采样相关性与图像重建质量的关系分析-Compressed sensing applications in the multi-base synthetic aperture radar, relationship analysis on sampling correlation with the quality of image reconstruction
00759919
- his paper presents the analysis of real power system events recorded at a light industrial site to determine the effect of a shunt active filter on power quality. The shunt active fdter is shown to improve power quality by lowering the disto
Short-duration-power_CS
- 根据压缩传感(Compressed Sensing，cs)N论，首次提出了短时电能质量扰动信号的压缩采样方法，该方法突破了奈奎斯特采样频率的限制，实现了低于奈奎斯特采样频率的低速率采样。文中对比分析了CS理论与传统采样理论，研究了cS短时电能质量信号压缩采样的实现方法，包括：测量矩阵的构建、稀疏基的选取和电能质量信号快速贝叶斯匹配追踪重构算法(FBMP)-Compressed sensing ( Compressed Sensing , cs ) N theory , first propose
paper1
- Tradeoff Analysis of Delay-Power-CSIT Quality of Dynamic BackPressure Algorithm for Energy Efficient OFDM Systems
cusum-algorithm
- In statistical quality control, the CUSUM (or cumulative sum control chart) is a sequential analysis technique developed by E. S. Page of the University of Cambridge. It is typically used for monitoring change detection.[1] CUSUM was announced in Bio