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FuzzyImmunePID
一个时滞系统的模糊免疫PID控制(实例)(Fuzzy immune PID control for a time delay system(An example))
- 2010-08-17 11:13:12下载
- 积分：1
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02_SynthesizableMATLAB
Lab 2 – Synthesizable MATLAB
This lab exercise will explore the effects that different MATLAB coding styles have on hardware. The lab has two parts, each of which begins with a short introduction. This lab exercise is based on the simple MATLAB FIR filter model shown below:(Lab 2- Synthesizable MATLABThis lab exercise will explore the effects that different MATLAB coding styles have on hardware. The lab has two parts, each of which begins with a short introduction. This lab exercise is based on the simple MATLAB FIR filter model shown below:)
- 2007-04-18 12:49:18下载
- 积分：1
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m
说明： consists of communication system
- 2012-07-27 14:13:18下载
- 积分：1
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morphology
this code extract the ellipse from noisy image by morphology method
- 2014-01-12 03:37:25下载
- 积分：1
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Hhossa_ddi
高阶谱分析工具箱，有常见的参数模模型高阶谱估计，DOA估计与时延估计
(Higher order spectral analysis toolbox, common parameter-mode model of higher order spectral estimation of DOA estimation and delay estimation)
- 2012-07-17 23:10:21下载
- 积分：1
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Alamoutiwork
程序的主要功能是做了一定范围的信噪比下，对每个信噪比：随机信号QPSK调制；
根据Alamouti方案的矩阵进行编码；发送信号经过瑞利信道和加入高斯白噪声；
接收信号采用最大比合并的方法；最后对合并信号进行最大似然判决并求误符号率。
结果表明10^-3对应大约12->13dB(Procedure main function is to do a certain range of SNR for each signal to noise ratio: random signal QPSK modulation program in accordance with Alamouti coding matrix send signals through Rayleigh channel and adding Gaussian white noise received signal using maximal-ratio combining method Finally the combined signal and the maximum likelihood decision for symbol error rate. The results showed that about 10 ^-3 corresponds to 12-> 13dB)
- 2007-11-01 00:32:10下载
- 积分：1
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BallbeamSystem
说明： 我的智能控制作业，球—横木控制系统matlab仿真程序。程序及仿真模型，结果都有。(intelligent control operations, the ball-ledger control system Matlab simulation program. Procedures and simulation models, results have.)
- 2006-03-03 10:12:08下载
- 积分：1
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1807.01622
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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simLLRvsHD_
simulation LLR and Hardware
- 2009-11-25 20:17:35下载
- 积分：1
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chirp-
线性调频信号的脉冲压缩，合成孔径雷达（SAR）的第一个大作业的程序(the compression of chirp signal)
- 2013-12-03 16:03:44下载
- 积分：1
