這是一個Quartus的工程文件和verilog代碼，講如何把memory 變成vector
上傳時間： 2017-03-07
上傳用戶：趙云興
In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined.
標簽： mean-square multiuser receiver project
上傳時間： 2014-11-21
上傳用戶：ywqaxiwang
IML package provides efficient routines to solve nonsingular systems of linear equations, certified solve any shape systems of linear equations, and perform mod p matrix operations, such as computing row-echelon form, determinant, rank profile, inverse of a mod p matrix.
標簽： nonsingular efficient equations certifie
上傳時間： 2017-03-21
上傳用戶：leixinzhuo
一個全排列算法的實現，利用了C++模板技術以及STL 中的 Vector
標簽： 算法
上傳時間： 2013-12-29
上傳用戶：gmh1314
c pgm to find redundant paths in a graph.Many fault-tolerant network algorithms rely on an underlying assumption that there are possibly distinct network paths between a source-destination pair. Given a directed graph as input, write a program that uses depth-first search to determine all such paths. Note that, these paths are not vertex-disjoint i.e., the vertices may repeat but they are all edge-disjoint i.e., no two paths have the same edges. The input is the adjacency matrix of a directed acyclic graph and a pair(s) of source and destination vertices and the output should be the number of such disjoint paths and the paths themselves on separate lines. In case of multiple paths the output should be in order of paths with minimum vertices first. In case of tie the vertex number should be taken in consideration for ordering.
標簽： fault-tolerant algorithms redundant underlyin
上傳時間： 2013-12-18
上傳用戶：jkhjkh1982
Shortest Paths with Multiplicative Cost. In a given undirected graph, the path cost is measured as a product of all the edges in the path. The weights are rational numbers (e.g., 0.25, 0.75, 3.75 etc) or integers (2, 3). There are no negative edges. Given such a graph as input, you are to output the shortest path between any two given vertices. Input is the adjacency matrix and the two vertices. You must output the path.
標簽： Multiplicative undirected Shortest measured
上傳時間： 2017-04-08
上傳用戶：邶刖
In some graphs, the shortest path is given by optimizing two different metrics: the sum of weights of the edges and the number of edges. For example: if two paths with equal cost exist then, the path with the least number of edges is chosen as the shortest path. Given this metric, you have find out the shortest path between a given pair of vertices in the input graph. The output should be the number of edges on the path, the cost of the shortest path, and the path itself. Input is the adjacency matrix and the two vertices.
標簽： optimizing different the shortest
上傳時間： 2014-10-25
上傳用戶：1159797854
Edge Disjoint Cycles. You are given an input graph that is either directed or undirected. Write a program that reads in a vertex number and lists the number of edge disjoint cycles that start and end at this vertex. The output should also list the edges in each of the cycle discovered. Input will be the adjacency matrix preceded by a 0 or 1 representing Directed or Undirected graphs respectively.
標簽： undirected Disjoint directed Cycles
上傳時間： 2017-04-08
上傳用戶：13188549192
The angles in degrees of the two spatially propagating signals Compute the array response vectors of the two signals Compute the true covariance matrix
標簽： propagating the spatially response
上傳時間： 2014-01-24
上傳用戶：1966640071
統計模式識別工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines
標簽： Statistical Recognition Pattern Toolbox
上傳時間： 2014-01-03
上傳用戶：璇珠官人
