LMSandRLS

deep learning一般是学习的层次结构，它也是有一定理论依据的，即模拟人脑的大脑皮层工作，因为大脑皮层的视觉区域也是分层次工作的，越底层的视觉皮层对那些底层特征就越敏感。综上所述，feature learning有这么多应用需求的驱动和生物神经理论上的支持，注定它能够在AI领域中发挥一定的作用。一些实验表明，有些feature learning学习到的特征几乎比所有其它的特征效果要好，比如本文中的ISA模型就是其中一个。(deep learning hierarchy of learning, it is also a certain theoretical basis that simulate the human brain' s cerebral cortex, visual areas of the cerebral cortex is hierarchical work, the more the bottom of the visual cortex is more sensitive to those underlying characteristics . In summary, feature learning so many application needs the support of the drive and biological neural theoretically doomed it to be able to play a certain role in the field of AI. Some experiments show that some feature learning learning to feature almost better than all the other features of the effect of the ISA model such as this is one.)

求解MATLAB单纯型法程序求解MATLAB单纯型法程序(MATLAB simplex method for solving process-based method for solving simple MATLAB program)

该源码是关于模糊控制算法的MATLAB实现的，内容包括被控系统模糊建模，输入变量转换到论域，模糊规则库的建立等。(the source of fuzzy control algorithm in MATLAB, including Fuzzy charged modeling, conversion of input variables domain, the fuzzy rules for the establishment of such.)

数字信号处理中采样定理和卷积定理的验证，简单易懂的matlab源码，(Validation sampling theorem and convolution theorem of the digital signal processing in the matlab source code, easy to understand)

PID controller design

this is increment area method to forecast sedimentation in dams reserviour

A working setup that focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [

用牛顿-拉夫逊算法求解线路中的潮流运算，能够求解各节点电压降，线路网络损耗(Newton- Raphson algorithm for computing the trend line, each node can solve the voltage drop line network losses)

格拉姆-施密特正交化法--还可以计算方阵的QR分解，十分方便，十分简洁！！(Gramm- Schmidt method- can also calculate the square QR decomposition, very convenient, very simple! !)

online library is a project for b.tech students