Directed Graph Model

The Directed Graph Model

A directed graph G consists of a set of vertices V and an edge set E of ordered pairs of vertices. For our purposes, each vertex corresponds to an artist. If ( Y , X ) ∈ E (Y,X) \in E (Y,X)E then there is an arrow pointing from Y Y Y to X X X, called edge.

For instance, V = { i n f l u e n c e r , f o l l o w e r } , E = { ( i n f l u e n c e r , f o l l o w e r ) } V=\{influencer,follower\}, E = \{(influencer,follower)\} V={influencer,follower},E={(influencer,follower)}, The relationship between influencers and followers can be represented in the graph G consist of V and E.

Construct a Directed Graph

In the directed graph G, each edge (arrow) represents a binary relation where a vertex points to another.
An example will explain this modeling process in more detail:

In Figure:G(Example), the vertex set contains 1 , 2 , 3 , 4 , 5 , 6 1, 2, 3, 4, 5, 6 1,2,3,4,5,6 .
The relationship of vertex includes:

  • 6 points to 1,
  • 1 points to 2 and 5,
  • 2 points to 3,
  • 3 points to 4,
  • 4 points to 2 and 7.

Strongly Connected Component(SCC)

Strongly Connected: A directed graph is strongly connected if each vertex is reachable from other vertex.
Strongly Connected Components: Strongly connected is a binary equivalence relation, and the induced subgraphs of its equivalence classes are called strongly connected components.
s c c ( G ) scc(G) scc(G): The set of strongly connected components in graph G.
In Figure: G(Eample), s c c ( G ) = { [ 2 , 3 , 4 ] } scc(G) = \{[2,3,4]\} scc(G)={[2,3,4]}

Directed Acyclic Graph(DAG)

If each strongly connected component of the original graph contract to a single vertex, the resulting graph is a directed acyclic graph called directed acyclic graph(DAG).

Find the strongly connected components( s c c ( G ) scc(G) scc(G)) in a directed graph G, replace the circle in G with the strongly connected components as a vertex, and get new directed graph C(must be DAG).

极化码(Polar Code)是由土耳其科学家Erdal Arıkan在2009年提出的一种新型纠错编码技术。它通过利用信道的极化现象,将虚拟信道分为误码率接近0和接近1/2的两类。在编码设计中,数据被放置在误码率极低的信道上,从而实现高效的数据传输。极化码的主要优势在于其理论编码容量能够达到香农限,并且构造方法较为简单。 MATLAB是一种功能强大的数学计算和编程工具,广泛应用于科学研究和工程领域。在极化码的研究中,MATLAB可用于构建编码和解码算法,模拟数据在不同信道条件下的传输效果,验证理论性能,并优化相关参数。 SC(Successive Cancellation,逐位取消)译码是极化码的基本解码方法。它从最可靠的比特开始,依次解码每个虚拟信道,且每个比特的解码结果会影响后续比特的解码,因为它们之间存在依赖关系。虽然SC译码的实现较为简单,但其计算复杂度较高,随着码长的增加,解码时间会线性增长。 SCL(Successive Cancellation List,逐位取消列表)译码是SC译码的改进版本。它通过引入列表机制,同时处理多个路径,从而增强了错误校正能力,并在一定程度上降低了错误率。与SC译码相比,SCL译码虽然需要消耗更多的计算资源,但能够提供更好的性能。 一个完整的MATLAB仿真资源通常包含以下内容: 编码模块:用于实现极化码的生成,包括码字构造和极化矩阵操作等。 信道模型:用于模拟各种通信信道,例如AWGN(加性高斯白噪声)信道或衰落信道。 SC/SCL译码模块:包含SC译码和SCL译码的算法实现。 误码率(BER)计算:通过比较发送和接收的码字,计算误码率,以评估编码性能。 性能曲线绘制:绘制误码率与信噪比(SNR)之间的关系曲线,展示不同译码策略的性能差异。 使用说明:指导用户如何运行仿真,理解代码结构,以及如何调整参数以进行自定义实验。 代码注
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