sarRCM

mimo系统中的DBOST编码的详细源程序(MIMO system DBOST detailed source coding)

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.)

求解包装动力学在受到脉冲下的冲击谱,来算具体响应规律 (response shock spectrum)

模式识别中txt数据的导入算法，大家看看，做个参考(Pattern recognition algorithms in the txt data import, we look to be a reference)

《精通MATLAB—综合辅导与指南》，word格式的，可读性很强，适合初级学习人员使用。("proficient MATLAB-comprehensive counseling and guidance", word format, readability strong, suitable for junior staff learn to use.)

用matlab中的工具箱函数来解决遗传算法问题，以及进行若干实例讲解 (using Matlab toolbox functions of the genetic algorithm to solve the problem, as well as a number of examples to explain)

非常好的关于,BP网络层数设计工作，有很好的应用价值。(Very good BP Neural network,Very good application)

2D FDTD in a unitless space with open boundary with matrix update instead of for loops

Ejemplo para Grossberg convertir una entrada digital a analogica

高阶谱双谱程序，非常实用的双谱例程供你参考(Order spectrum bispectral procedures, very practical double spectral routines for your reference)