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binary_add
binary addition calculator
can add any two bit strings, the inputs must be of same length
- 2010-06-30 03:12:01下载
- 积分：1
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Documentation
some matlab codes for image processing
- 2009-06-02 15:50:09下载
- 积分：1
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xiaobofenxi1
说明： 有关MATLAB中小波的分析，大家一起分享，希望能对你有帮助(The MATLAB' s edge detection process, to share with everyone, hope you can help)
- 2010-04-24 18:15:09下载
- 积分：1
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signal-modulate
用于信号调制的函数，可对自然码和格雷码的性能进行比较。(Function for signal modulation of natural code and gray code)
- 2012-05-02 16:14:20下载
- 积分：1
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Swarm-Tracking
国外著名控制专著《extremum seeking control and application》输出跟踪控制案例源码，采用matlab编写，对研究极值搜索控制理论非常有帮助(a well-known book about system control 《extremum seeking control and application》output tracking control matlab code, it will benefit to study the extremum seeking control theory for people)
- 2013-09-15 14:55:19下载
- 积分：1
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Matlab.rar-(2.9-MB)
Matlab的很有用的常用经典算法，包括数据分析，绘图等(Classical algorithm commonly used in Matlab)
- 2011-11-29 17:09:24下载
- 积分：1
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IS95_baseband_simulation
his packet is a IS-95 baseband simulation for 1 data channel of 9.6 KBps rate.
The simulation is written for static channel and AWGN noise. The packet include:
1) Packet Builder (Viterbi Encoding, Interleaver, PN generation)
2) Modulator (RRC filter)
3) Demodulator (Matched Filter, RAKE receiver)
4) Receiver (HD or SD) (Deinterleaver, Viterbi Decoder).
You should run "Simulation.m" function that include all modules.(his packet is a IS-95 baseband simulation f or a data channel rate of 9.6 KBps. The simulatio n is written for static channel and AWGN noise. T he packet include : 1) Packet Builder (Viterbi Encoding. Interleaver. PN generation) 2) Modulator (RRC filter) 3) Dem odulator (Matched Filter, RAKE receiver) 4) Receiver (HD or SD) (Deinterl eaver. Viterbi Decoder). You should run "Simulation. m "function that include all modules.)
- 2007-03-14 18:36:48下载
- 积分：1
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delphi
DELPHI环境下MATLAB和数据库之间的数据通讯(DELPHI environment MATLAB and data communication between the database)
- 2011-02-06 21:51:37下载
- 积分：1
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1807.01622
说明： 深度神经网络在函数近似中表现优越，然而需要从头开始训练。另一方面，贝叶斯方法，像高斯过程（GPs），可以利用利用先验知识在测试阶段进行快速推理。然而，高斯过程的计算量很大，也很难设计出合适的先验。本篇论文中我们提出了一种神经模型，条件神经过程（CNPs），可以结合这两者的优点。CNPs受灵活的随机过程的启发，比如GPs，但是结构是神经网络，并且通过梯度下降训练。CNPs通过很少的数据训练后就可以进行准确的预测，然后扩展到复杂函数和大数据集。我们证明了这个方法在一些典型的机器学习任务上面的的表现和功能，比如回归，分类和图像补全(Deep neural networks perform well in function approximation, but they need to be trained from scratch. On the other hand, Bayesian methods, such as Gauss Process (GPs), can make use of prior knowledge to conduct rapid reasoning in the testing stage. However, the calculation of Gauss process is very heavy, and it is difficult to design a suitable priori. In this paper, we propose a neural model, conditional neural processes (CNPs), which can combine the advantages of both. CNPs are inspired by flexible stochastic processes, such as GPs, but are structured as neural networks and trained by gradient descent. CNPs can predict accurately with very little data training, and then extend to complex functions and large data sets. We demonstrate the performance and functions of this method on some typical machine learning tasks, such as regression, classification and image completion.)
- 2020-06-23 22:20:02下载
- 积分：1
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source
使用Matlab R2009b进行数字音频调时处理编程(Using Matlab R2009b transfer digital audio processing program when)
- 2010-06-27 11:41:35下载
- 积分：1
