adaptive

机械手运动学方程求解 。分别输入机械臂的末端坐标，求出第一组角度解 ，第二组角度解。(Manipulator kinematics equation. Manipulator, respectively, the end of input coordinates, the perspective of the first group obtained solution, and the second group of solutions perspective.)

用matlab实现的windows属性设置软件，能够设置windows里的各个参数(Using matlab to achieve the windows property software, you can set various parameters in the windows)

SHORTEST PATH PROGRAM

通过选择法，选出一组数据，导入到新建的数组中(By selecting the method to elect a set of data, into the new array)

该程序介绍了有关八叉树编码的基本编程知识，对于初级学者易懂易学。(This program introduces the octree encoding basic programming knowledge, which ishelpful for junior scholars to understand.)

MATLAB CODE FOR SPEECH PROCESSING

BAnet实现代码,并且保存成txt文件。(BAnet implement code use matlab,and save as a txt file ,you also can translate other language using this code it must be useful,)

阵列信号处理的各种算法matlab程序，包含MUSIC、ESPRIT及变形等各种算法。(Array signal processing algorithms matlab procedures, including MUSIC, ESPRIT and deformation algorithms.)

Matlab能够通过sound函数来实现演奏歌曲，而且音调的高低是和频率有关，所以我们在进行音乐合成时需按音调来查所对应的频率，再按曲谱控制节奏长度，再利用sound函数播放由不同频率的正弦波合成的声音，于是就可以利用Matlab演奏歌曲了。(Music synthesis)

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.)