simulink-QPSK-bpsk

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.)

向量机算法中的核函数向量机算法中的核函数向量机算法中的核函数(SVM kernel function)

this support file can be used in matlab by copying it to the current working directory. using this u can access commands like zvect etc.

this is a matlab code source

We consider the scheduling of simple linear deteriorating jobs on parallel machines a new perspective based on game theory. In scheduling, jobs are often controlled by independent and selfish agents, in which each agent tries to a machine for processing that optimizes its own payoff while ignoring the others. We formalize this situation as a game in which the players are job owners, the strategies are machines, and a player’s utility is inversely proportional to the total completion time of the machine selected by the agent. The price of anarchy is the ratio between the worst-case equilibrium makespan and the optimal makespan. In this paper, we design a game theoretic approximation algorithm Aand prove that it converges to a pure-strategy Nash equilibrium in a linear number of rounds. We also derive the upper bound on the price of anarchy of Aand further show that the ratio obtained by Ais tight. Finally, we analyze the time complexity of the proposed algorithm

改进后的直接转矩控制系统，绝对能用。matlan/simulink7.4(Improved direct torque control system, the absolute use. matlan/simulink7.4)

emd算法 还是比较详细准确的算法 英文注释(emd algorithm is more detailed and accurate algorithm for English Notes)

LDPC码的matlab仿真程序，希望对大家有用，不客气，(LDPC codes matlab simulation program, in the hope that useful, at worst,)

基于matlab的pam仿真 附带源代码 (pam (using matlab) 基于matlab的pam仿真)

求连续函数的卷积，利用matlab中的conv函数实现(Seek a continuous function of the convolution, using the conv function in Matlab to achieve)