This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
Write a program to decide if a graph has a cycle or not. The given graph can be a directed or undirected graph, which is indicated at the time of reading the input (0 for directed graph and 1 for undirected graphs). The input is given as an adjacency list.
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.
The first decision, that has to be made for the AVR platform, is to select the
development environment you want to use, either ImageCraft s ICCAVR or
GNU s AVR-GCC. The commercial ImageCraft Compiler offers an advanced IDE
and is the first choice of most professional developers using a Windows PC. The
GNU compiler is available for Linux and Windows.
