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RSS订阅原创 求出部分有序数组中的最大子数组(第一次出现)的长度及位置 （c++实现）
在复习数据结构是，看到书中有这么一个题目：求出部分有序数组中的最大子数组(第一次出现)的长度及位置 然后就简单的实现了下，难免有疏漏之处，还望见谅和指出，在此谢过在CodeBlocks中编译通过，下面贴出代码：//找出部分有序的数组中连续有序最长的子数组#include using namespace std;void lenth(int a[], int n,
2015-04-26 13:19:35
785
原创 c++ 实现单向链表
终于有时间来复习复习数据结构了，使用的教材是《c++数据结构与算法》第四版，下面是在复习过程中一些简单的实现，权当练手的笔记和温习吧。可能有疏漏之处，还望见谅和指出，在此谢过 O(∩_∩)O~下面把代码贴出来，其中有很详细的注释，在CodeBlocks中编译通过在IntSLLish.h头文件中定义了链表节点IntSLLNode和链表IntSLList，其中head和tail分
2015-04-26 12:57:45
611
原创 积分图像matlab实现(The implementation of integral image by matlab)
在看图像处理的相关文献时看到了图像积分(integral image)这个方法,觉得挺有意思的，于是就动手实现了这个算法，实现的可能还不够优化 ^_^对于图像积分概念，下面这篇博客解释的比较详细：http://blog.163.com/pz124578@126/blog/static/23522694201332752444805/在这，我就不具体阐述了其过程了，有兴趣的可以看看上面
2014-11-18 15:12:01
7129
3
转载 小波变换与傅里叶变换
这是在一个论坛看的帖子，如果有人问我，如果傅里叶变换没有学好（深入理解概念），是否能学好小波。答案是否定的。如果有人还问我，如果第一代小波变换没学好，能否学好第二代小波变换。答案依然是否定的。但若你问我，没学好傅里叶变换，能否操作（编程）小波变换，或是没学好第一代小波，能否操作二代小波变换，答案是肯定的。一、基的概念我们要明确的是基的概念。两者都是基，信
2014-08-01 16:09:29
1147
原创 java实现字符串左旋转
这是原文的第一道题.原文网址：http://blog.youkuaiyun.com/v_july_v/article/details/17303459 有兴趣的可以去看看没有看原博主的答案，这是自己的答案以左移两位为例原始顺序：a b c d e f g左移两位后：c d e f g a b方法一的过程：可以先移动一位：b c d
2013-12-17 22:21:32
820
原创 java模拟链表和栈以及简单实现
在我的新浪博客中也有。。。呵呵小弟初来乍到，第一次写博客，估计写的不会好，还望多多包涵···:-)昨天看了一篇关于面试算法的java描述的数据结构，发现其中存在一些问题，至少在我看来，仅一家之言哈 :-) 欢迎讨论···O(∩_∩)O谢谢 下面开始正题：1、关于链表和栈的示意图，如下图（ps：不再严格区分首节点和头节点，不要拘泥于书本，仅作示意 :-) ）
2013-12-01 13:03:47
904
Matlab_2014b_Crack（2015-04-09）
包括32位与64位pojie文件与安装步骤
亲测32位可完整pojie安装！
ver
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MATLAB Version: 8.4.0.150421 (R2014b)
MATLAB License Number: 409xxx
Operating System: Microsoft Windows 7 旗舰版 Version 6.1 (Build 7601: Service Pack 1)
Java Version: Java 1.7.0_11-b21 with Oracle Corporation Java HotSpot(TM) Client VM mixed mode
---------------------------------------------------------------------------------------------
MATLAB Version 8.4 (R2014b)
Simulink Version 8.4 (R2014b)
Aerospace Blockset Version 3.14 (R2014b)
Aerospace Toolbox Version 2.14 (R2014b)
Bioinformatics Toolbox Version 4.5 (R2014b)
Communications System Toolbox Version 5.7 (R2014b)
Computer Vision System Toolbox Version 6.1 (R2014b)
Control System Toolbox Version 9.8 (R2014b)
Curve Fitting Toolbox Version 3.5 (R2014b)
DO Qualification Kit Version 2.4 (R2014b)
DSP System Toolbox Version 8.7 (R2014b)
Data Acquisition Toolbox Version 3.6 (R2014b)
Database Toolbox Version 5.2 (R2014b)
Datafeed Toolbox Version 5.0 (R2014b)
Econometrics Toolbox Version 3.1 (R2014b)
Embedded Coder Version 6.7 (R2014b)
Filter Design HDL Coder Version 2.9.6 (R2014b)
Financial Instruments Toolbox Version 2.0 (R2014b)
Financial Toolbox Version 5.4 (R2014b)
Fixed-Point Designer Version 4.3 (R2014b)
Fuzzy Logic Toolbox Version 2.2.20 (R2014b)
Gauges Blockset Version 2.0.9 (R2014b)
Global Optimization Toolbox Version 3.3 (R2014b)
HDL Coder Version 3.5 (R2014b)
HDL Verifier Version 4.5 (R2014b)
IEC Certification Kit Version 3.4 (R2014b)
Image Acquisition Toolbox Version 4.8 (R2014b)
Image Processing Toolbox Version 9.1 (R2014b)
Instrument Control Toolbox Version 3.6 (R2014b)
LTE System Toolbox Version 1.2 (R2014b)
MATLAB Builder EX Version 2.5.1 (R2014b)
MATLAB Builder JA Version 2.3.2 (R2014b)
MATLAB Builder NE Version 4.2.2 (R2014b)
MATLAB Coder Version 2.7 (R2014b)
MATLAB Compiler Version 5.2 (R2014b)
MATLAB Distributed Computing Server Version 6.5 (R2014b)
MATLAB Report Generator Version 4.0 (R2014b)
Mapping Toolbox Version 4.0.2 (R2014b)
Model Predictive Control Toolbox Version 5.0 (R2014b)
Model-Based Calibration Toolbox Version 4.8 (R2014b)
Neural Network Toolbox Version 8.2.1 (R2014b)
OPC Toolbox Version 3.3.2 (R2014b)
Optimization Toolbox Version 7.1 (R2014b)
Parallel Computing Toolbox Version 6.5 (R2014b)
Partial Differential Equation Toolbox Version 1.5 (R2014b)
Phased Array System Toolbox Version 2.3 (R2014b)
Polyspace Bug Finder Version 1.2 (R2014b)
Polyspace Code Prover Version 9.2 (R2014b)
RF Toolbox Version 2.15 (R2014b)
Real-Time Windows Target Version 4.5 (R2014b)
Robust Control Toolbox Version 5.2 (R2014b)
Signal Processing Toolbox Version 6.22 (R2014b)
SimBiology Version 5.1 (R2014b)
SimDriveline Version 2.7 (R2014b)
SimElectronics Version 2.6 (R2014b)
SimEvents Version 4.3.3 (R2014b)
SimHydraulics Version 1.15 (R2014b)
SimMechanics Version 4.5 (R2014b)
SimPowerSystems Version 6.2 (R2014b)
SimRF Version 4.3 (R2014b)
Simscape Version 3.12 (R2014b)
Simulink 3D Animation Version 7.2 (R2014b)
Simulink Code Inspector Version 2.2 (R2014b)
Simulink Coder Version 8.7 (R2014b)
Simulink Control Design Version 4.1 (R2014b)
Simulink Design Optimization Version 2.6 (R2014b)
Simulink Design Verifier Version 2.7 (R2014b)
Simulink PLC Coder Version 1.8 (R2014b)
Simulink Real-Time Version 6.1 (R2014b)
Simulink Report Generator Version 4.0 (R2014b)
Simulink Verification and Validation Version 3.8 (R2014b)
Spreadsheet Link EX Version 3.2.2 (R2014b)
Stateflow Version 8.4 (R2014b)
Statistics Toolbox Version 9.1 (R2014b)
Symbolic Math Toolbox Version 6.1 (R2014b)
System Identification Toolbox Version 9.1 (R2014b)
SystemTest Version 2.6.8 (R2014b)
Trading Toolbox Version 2.1.1 (R2014b)
Vehicle Network Toolbox Version 2.3 (R2014b)
Wavelet Toolbox Version 4.14 (R2014b)
>>
2015-04-09
MahNMF Manhattan Non-negative Matrix Factorization
MahNMF Manhattan Non-negative Matrix Factorization code
% Manhattan Non-negative Matrix Factorization.
% ManhNMF: Matlab Code for Efficient Robust Manhattan NMF Solver
% Reference
% [1] N. Guan, D. Tao, Z. Luo, and J. Shawe-taylor, "MahNMF: Manhattan
% Non-negative Matrix Factorization," arXiv:1207.3438v1, 2012.
% [2] N. Guan, D. Tao, Z. Luo, and J. Shawe-taylor, "MahNMF: Manhattan
% Non-negative Matrix Factorization," Submitted to Journal of Machine Learning Research, 2013.
% The model is X \approx W^TH, where X, W, and H are defined as follows:
% X (m x n): data matrix including n samples in m-dimensional space;
% W (r x m): basis matrix including r bases in m-dimensional space;
% H (r x n): coefficients matrix includeing n encodings in r-dimensional space.
% Written by Naiyang Guan (ny.guan@gmail.com)
% Copyright 2012-2014 by Naiyang Guan and Dacheng Tao
% Modified at Jan. 28 2013
% <Inputs>
% X : Input data matrix (m x n)
% r : Target low-rank
%
% (Below are optional arguments: can be set by providing name-value pairs)
% MAX_ITER : Maximum number of iterations. Default is 1,000.
% MIN_ITER : Minimum number of iterations. Default is 10.
% MAX_TIME : Maximum amount of time in seconds. Default is 100,000.
% W_INIT : (m x r) initial value for W.
% H_INIT : (r x n) initial value for H.
% LAM_INIT : initial value of smoothness parameter. Default is 1.
% MDL_TYPE : Model type (Default is 'PLAIN'),
% 'PLAIN' - MahNMF (min{||X-W^T*H||_1,s.t.,W >= 0 and H >= 0}.),
% 'BXC' - Box Constrained MahNMF (min{||X-W^T*H||_1,s.t.,1 >= W >= 0 and 1 >= H >= 0}.),
% 'MNR' - Manifold Regularized MahNMF
% (min{||X-W^T*H||_1+.5*beta*TR(H*Lp*H^T),s.t.,W >= 0 and H >= 0}.),
% 'GSP' - Group Sparse MahNMF
% (min{||X-W^T*H||_1+.5*beta*\sum_{g\in G}||W^[g]||_{1,p},s.t.,W >= 0 and H >= 0}.),
% 'SYM' - Symmetric MahNMF (min{||X-H*H^T||_1,s.t., H >= 0}.).
% ALG_TYPE : Algorithm type (Default is 'AGD'),
% 'AGD' - Accelerated Gradient Descent,
% 'RRI' - Rank-one Residue Iteration.
% BETA : Tradeoff parameter over regularization term. Default is 1e-3.
% SIM_MTX : Similarity matrix constructed by 'constructW'.
% GPP_MTX : Group pattern for boundary of all groups.
% TOL_INNR : Stopping tolerance of inner iterations. Default is 1e-2.
% TOL_OUTR : Stopping tolerance of outer iterations. Default is 1e-3.
% If you want to obtain a more accurate solution, decrease TOL_INNR or TOL_OUTR and increase MAX_ITER at the same time.
% VB_OUTR : 0 (default) - No debugging information is collected.
% 1 (debugging purpose) - History of computation is returned by 'HIS' variable.
% 2 (debugging purpose) - History of computation is additionally printed on screen.
% VB_INNR : 0 (default) - No debugging information is collected.
% 1 (debugging purpose) - History of computation is returned by 'HIS' variable.
% 2 (debugging purpose) - History of computation is additionally printed on screen.
% <Outputs>
% W : Obtained basis matrix (r x m).
% H : Obtained coefficients matrix (r x n).
% iter : Number of iterations.
% elapse : CPU time in seconds.
% HIS : (debugging purpose) History of computation,
% niter - total iteration number spent for Nesterov's optimal
% gradient method,
% cpus - CPU seconds at iteration rounds,
% objf - objective function values at iteration rounds,
% dlta - stopping criteria of block coordinate descent.
%
% <Usage Examples>
% >>X=rand(1000,500);
% >>ManhNMF(X,10);
% >>ManhNMF(X,20,'verbose',1);
% >>ManhNMF(X,30,'verbose',2,'w_init',rand(r,m));
% >>ManhNMF(X,5,'verbose',2,'tol_outr',1e-5);
% Note: other files 'GetStopCriterion.m', 'ApproxFunC.m', and 'wmedianf.mexw32' should be included under the same
% directory as this code.
2015-04-22
谢希仁 计算机网络 第七版 随书课件
本书的特点是概念准确、论述严谨、内容新颖、图文并茂，突出基本原理和基本概念的阐述，同时力图反映计算机网络的一些最新发展。本书可供电气信息类和计算机类专业的大学本科生和研究生使用，对从事计算机网络工作的工程技术人员也有参考价值。
PS:其实作者在书中提供的了ppt的下载链接，只是很多同学没有注意到而已，看到一些分享者的资源分都太高了，所以就上传了原版、低资源分；同时还附上原下载连接：http://yx.51zhy.cn/mtrcsRes/phei_cnetwork.jsp 大家自行选择O(∩_∩)O
2018-01-14
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