There is an example of how to use the LDPC encode/decode with AWGN
channel model in files .\ldpc_decode.m and .\GFq\ldpc_decode.m.
There are a few parity check matrices available in the code but
you can use other matrices provided you have enough memory to load
them. I suggest checking out matrices in Alist format available on
David MacKay s web site.You will need to have access to a MEX compiler
to be able to use a few functions written in C.
LDPC的仿真代碼
Problem Statement
You are given a string input. You are to find the longest substring of input such that the reversal of the substring is also a substring of input. In case of a tie, return the string that occurs earliest in input.
Definition
Class: ReverseSubstring
Method: findReversed
Parameters: string
Returns: string
Method signature: string findReversed(string input)
(be sure your method is public)
Notes
The substring and its reversal may overlap partially or completely.
The entire original string is itself a valid substring (see example 4).
Constraints
input will contain between 1 and 50 characters, inclusive.
Each character of input will be an uppercase letter ( A - Z ).
Examples
0)
"XBCDEFYWFEDCBZ"
Returns: "BCDEF"
We see that the reverse of BCDEF is FEDCB, which appears later in the string.
1)
In the process of copper flash smelting, lining temperature of reaction shaft and its inner wall sluggish play a very important role in lining life. Up to now, however
his paper provides a tutorial and survey of methods for parameterizing
surfaces with a view to applications in geometric modelling and computer graphics.
We gather various concepts from di® erential geometry which are relevant to surface
mapping and use them to understand the strengths and weaknesses of the many
methods for parameterizing piecewise linear surfaces and their relationship to one
another.
How well do you really know Java? Are you a code sleuth? Have you ever spent days chasing a bug caused by a trap or pitfall in Java or its libraries? Do you like brainteasers? Then this is the book for you!
A one-dimensional calibration object consists of three or more collinear points with known relative positions.
It is generally believed that a camera can be calibrated only when a 1D calibration object is in planar motion or rotates
around a ¯ xed point. In this paper, it is proved that when a multi-camera is observing a 1D object undergoing general
rigid motions synchronously, the camera set can be linearly calibrated. A linear algorithm for the camera set calibration
is proposed，and then the linear estimation is further re¯ ned using the maximum likelihood criteria. The simulated and
real image experiments show that the proposed algorithm is valid and robust.
[輸入]
圖的頂點個數N，圖中頂點之間的關系及起點A和終點B
[輸出]
若A到B無路徑，則輸出“There is no path” 否則輸出A到B路徑上個頂點
[存儲結構]
圖采用鄰接矩陣的方式存儲。
[算法的基本思想]
采用廣度優先搜索的方法，從頂點A開始，依次訪問與A鄰接的頂點VA1,VA2,...,VAK, 訪問遍之后,若沒有訪問B，則繼續訪問與VA1鄰接的頂點VA11,VA12,...,VA1M，再訪問與VA2鄰接頂點...，如此下去，直至找到B，最先到達B點的路徑，一定是邊數最少的路徑。實現時采用隊列記錄被訪問過的頂點。每次訪問與隊頭頂點相鄰接的頂點，然后將隊頭頂點從隊列中刪去。若隊空，則說明到不存在通路。在訪問頂點過程中，每次把當前頂點的序號作為與其鄰接的未訪問的頂點的前驅頂點記錄下來，以便輸出時回溯。
#include<stdio.h>
int number //隊列類型
typedef struct{
int q[20]
