-
five_level_diode_clamped_pwmnikhil
five level diode clamp PWM.this is th e matlab simulink readyly usable file for PWM techinique
- 2011-05-23 17:04:02下载
- 积分:1
-
AntColonyClustering
利用Matlab开发的蚁群聚类算法,实例仿真过,比较好。(Developed using Matlab ant colony clustering algorithm, simulation examples too, is better.)
- 2011-07-03 21:09:37下载
- 积分:1
-
mmpsk
高效调制信号MPPSK,以及其功率谱特征(Efficient modulation signal MPPSK)
- 2014-08-08 22:14:16下载
- 积分:1
-
DEMC
说明: 基于蒙特卡罗马尔可夫链的差分遗传算法。算法有mc抽样改进,并用差分算法改进遗传优化算法(Difference genetic algorithm based on monte carlo markov chain. With MC sampling improvement algorithm difference algorithm improved genetic optimization algorithm)
- 2020-07-24 23:33:26下载
- 积分:1
-
extraction
该算法功能是运动视频帧目标检测,实验效果较好,值得一看(The algorithm feature is motion video frame target detection experiment better, worth a visit)
- 2013-08-12 08:25:12下载
- 积分:1
-
m8
chopper c simulink with matlab mm mm mm
- 2013-05-07 23:19:40下载
- 积分:1
-
add
加信噪声,经希尔伯特变换,在经过滤波器,产生单边带调幅信号(Plus letter noise, the Hilbert transform, through the filter, producing a single sideband amplitude modulation signal)
- 2012-11-27 22:33:53下载
- 积分:1
-
machenicaltestsignalprocessing_Matlab
机械测试信号处理 附书的matlab源码。(Mechanical testing signal processing matlab source attached to the book.)
- 2009-01-22 00:27:43下载
- 积分:1
-
spread-spectrum-correlation-properties-simulation
the two .m file used to generate m sequence and compute two sequences s correlation properties, for example to compute two gold sequences s correlations properties
- 2011-05-13 16:11:11下载
- 积分:1
-
Body-Area-Networks
一个身体部位比较模型的新方法网络(BAN)的,可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏,通过基于参数化到每个活动,每个学科和每个环节模型。使用错误,并明确之间权衡复杂性,在一个善良的适应措施相结合,显示有重要的影响时,适用于一系列典型的禁止通道数据。它是有不同的
在模式的选择的影响,以及它相关的复杂性,混合活动的“日常”的数据,设置活动相比,动态数据(例如步行)。平均路径损耗的不足,甚至位数的路径损失的措施,作为唯一的表征还强调“禁止通道。
(A new approach to compare models for body area
networks (BAN) that accommodates multiple links and multiple
subjects is presented. The absolute measure described allows
comparison across a spectrum of possible characterizations
ranging from single-parameter for an entire ensemble, through
to per-activity, per-subject and per-link based parameterized
models. The use of an explicit trade-off between error and
complexity, combined in a goodness-of-fit measure, is shown
to have important consequences when applied to a range of
typical BAN channel data. It is shown that there are different
implications in choice of model, and it’s associated complexity, for
mixed-activity “everyday” data, when compared with set-activity
dynamic data (e.g. walking). The deficiency of mean path loss,
or even median path loss measures, as a sole characterization of
the BAN channel is also highlighted.)
- 2011-12-01 21:21:32下载
- 积分:1