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[Algorithm] 算法设计五 DL : 0: 误差分析的方法有多种，例如，威点逊（J. H. Wilkison）针对的计算机的浮点运算提出的“向后误差分析”，这是一种先验估计误差的方法，较以往的“向前误差分析”在矩阵运算的舍入误差估计上有较好的结果，以而使矩阵的误差分析获得了突破性的进展，使不少用向前误差分析难于判定可靠性的数值方法获得新的进展。-error analysis by a number of means, for example, Granville point Morrison (J. H. Wilkison), referring to a computer's floating-point operations "backward error analysis," This is a priori estimation error method, compared to the previous "Forward Error Analysis" in the matrix computation Rounding error a better estimate on the results of a matrix so the error analysis of a breakthrough in the progress, many with forward error analysis difficult to determine the reliability of numerical methods to achieve new progress.
Date : 2025-12-19 Size : 77kb User : 周易
[Algorithm] jiefangcheng DL : 0: 这个也是我们在课程中一起做的，有不足的地方希望大家能够指出来，这样有利于大家的进步啊-This is a course we do together, deficiencies in the hope that we can point out. this is conducive to the progress we ah
Date : 2025-12-19 Size : 1kb User : 蒋小盾
[Algorithm] On-Line_MCMC_Bayesian_Model_Selection DL : 0: This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.-This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Date : 2025-12-19 Size : 215kb User : 晨间
[Algorithm] Reversible_Jump_MCMC_Bayesian_Model_Selection DL : 0: This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. -This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Date : 2025-12-19 Size : 340kb User : 晨间
[Algorithm] FFT DL : 0: 傅立叶变换源码；希望对学习傅立叶变换的程序员有所帮助；共同学习共同进步-Fourier Transform source wish to study Fourier Transform help programmers shared the common progress of study
Date : 2025-12-19 Size : 155kb User : lisi
[Algorithm] moncoes_3.0.0 DL : 0: 用c语言实现的压缩软件，简单易用。支持最大超过2G的文件。-Bzip compression in C , very easy to use , MD5 checksum , has support to files larger than 2 gb, has additional features not available in the original bzip2 files , compression decompression progress , pause , resume and cancel public domain
Date : 2025-12-19 Size : 76kb User : shepherd
[Algorithm] jiafaqi DL : 0: 加法器是产生数的和的装置。加数和被加数为输入，和数与进位为输出的装置为半加器。若加数、被加数与低位的进位数为输入，而和数与进位为输出则为全加器。-Adder is generated and the number of devices. Addend and the summand input, and digital and carry the output device is a half adder. If the addend, the progress of summand bits with low input, and several carry the output compared with the full adder.
Date : 2025-12-19 Size : 4kb User : 亢鑫
[Algorithm] SqlServerProject1 DL : 0: 随着科学技术的不断进步，计算机应用已经遍布整个社会的每个角落。目前社会正处于健保发展方兴未艾的时代，各医疗院所莫不兢兢业业地改善本身的体制或管理方式，以适应健保越来越严格的规范，在此背景下，本文论述了小型医院门诊管理信息系统，重点论述门诊挂号子系统和门诊财务管理子系统的设计实现，其中门诊挂号子系统主 -With the continuous progress of science and technology, computer applications have been all over every corner of society as a whole. The development community is now emerging era of health care, health care facilities all working hard to improve their structure or management, to meet increasingly stringent health care standards in this context, the paper discusses a small hospital out-patient management information system, focuses on out-patient registration subsystem and subsystem design and implementation of financial management, including patient registration subsystem is the main
Date : 2025-12-19 Size : 7kb User : 吴昊
[Algorithm] DYNAMC DL : 0: 蒸汽发生器动态计算，根据工况变化计算换热过程-Steam generator dynamics calculations, to calculate the progress of heat transfer conditions change
Date : 2025-12-19 Size : 10kb User : 董忠璇
[Algorithm] jianyijisuanqi DL : 0: 很简单的一个计算器，用java实现的，压缩包里面有所有的系统分析报告和每个阶段的详细进程报告，很适合做系统分析的初学者用-A very simple calculator using java, compressed packets inside all of the systems analysis and a detailed progress report for each stage. Very suitable for beginners to do system analysis
Date : 2025-12-19 Size : 168kb User : zcy
[Algorithm] fortran-files DL : 3: 文件1.f90：生成翼型naca0012的椭圆网格，并计算流场，给出壁面压力分布文件2.f90：maccormack方法解一维burger s方程文件3.f90：解一维laval管流动，其进出口均为亚音速，喉道后部有激波-File 1.f90: generate the airfoil naca0012 elliptical rotary cell, and calculate the flow field, given the wall pressure distribution file 2.f90: maccormack method to solve the burger' s equation, one-dimensional file 3.f90: solution of one-dimensional laval tube flow, its progress exports are subsonic, the back of the throat have shock
Date : 2025-12-19 Size : 5kb User : 李盈盈
[Algorithm] ffff DL : 0: 该方法可以达到很高的进度，数值积分精度高。-The method can achieve high progress, the high accuracy of numerical integration.
Date : 2025-12-19 Size : 1kb User : 王霞
[Algorithm] bbsa DL : 0: 自己编的，错误之处请多多指正，大家相互学习，共同进步-Own series, the wrong place, please correct me a lot, and we all learn from each other, the common progress
Date : 2025-12-19 Size : 574kb User : ma
[Algorithm] Astar_my DL : 0: A星算法，简单c++实现。仅供程序爱好者参考，若有同样爱好，欢迎交流，共同进步。-A star algorithm is simple c++ implementation. Program for lovers of reference, if the same hobby, welcomed the exchange and common progress.
Date : 2025-12-19 Size : 849kb User : john
[Algorithm] genetic-algorithm-cPP-implementation DL : 0: 简单的遗传算法c++实现，仅供参考，共同学习共同进步。-Simple genetic algorithm c++ implementation, for reference, shared learning and common progress.
Date : 2025-12-19 Size : 13.21mb User : john
[Algorithm] 9801drilling-data-progress DL : 0: 9801自然伽玛测井数据处理，品位计算以及成果数据打印-9801 natural gamma logging data processing, computing, and quality outcomes data printing
Date : 2025-12-19 Size : 1.23mb User : 江大宇
[Algorithm] Wavelet-packet- DL : 0: 小波包分解重构，说明很详细，望大家共同进步-Wavelet packet decomposition reconstruction, indicating very detailed, we hope common progress
Date : 2025-12-19 Size : 1kb User : haha
[Algorithm] LMS DL : 0: A learning management system (LMS) is a software application for the administration, documentation, tracking, reporting and delivery of educational courses or training programs.[1] They help the instructor deliver material to the students, administer tests and other assignments, track student progress, and manage record-keeping. LMSes are focused on online learning delivery but support a range of uses, acting as a platform for fully online courses, as well as several hybrid forms, such as blended learning and flipped classrooms. LMSes can be completemented by other learning technologies such as a training management system to manage instructor-led training or a Learning Record Store to store and track learning data.
Date : 2025-12-19 Size : 3kb User : Abdolmaleki
[Algorithm] C语言作业 DL : 0: 整理了一些算法包括随机数生成素数穷举判断(helloeveryone this is C++progress)
Date : 2025-12-19 Size : 5kb User : a389071432
[Algorithm] uniFiber2 DL : 4: 三维Hashin准则，分层准则的渐进损伤失效模拟子程序(progress damage evaluation)
Date : 2025-12-19 Size : 5kb User : Tony-Huo