An Adaptive Variational Mode Decomposition Technique with Differential Evolution Algorithm and Its Application Analysis

Variational mode decomposition is an adaptive nonrecursive signal decomposition and time-frequency distribution estimation method. The improper selection of the decomposition number will cause under decomposition or over decomposition, and the improper selection of the penalty factor will affect the bandwidth of modal components, so it is very necessary to look for the optimal parameter combination of the decomposition number and the penalty factor of variational mode decomposition. Hence, differential evolution algorithm is used to look for the optimization combination of the decomposition number and the penalty factor of variational mode decomposition because differential evolution algorithm has a good ability at global searching. The method is called adaptive variational mode decomposition technique with differential evolution algorithm. Application analysis and discussion of the adaptive variational mode decomposition technique with differential evolution algorithm are employed by combining with the experiment. The conclusions of the experiment are that the decomposition performance of the adaptive variational mode decomposition technique with differential evolution algorithm is better than that of variational mode decomposition.

The edge geodetic self decomposition number of a graph

Let G = (V, E) be a simple connected graph of order p and size q. A decomposition of a graph G is a collection π of edge-disjoint sub graphs G1, G2, ..., Gn of G such that every edge of G belongs to exactly one Gi , (1 ≤ i ≤ n) . The decomposition π = {G1, G2, ....Gn } of a connected graph G is said to be an edge geodetic self decomposi- tion if ge (Gi ) = ge (G), (1 ≤ i ≤ n).The maximum cardinality of π is called the edge geodetic self decomposition number of G and is denoted by πsge (G), where ge (G) is the edge geodetic number of G. Some general properties satisfied by this concept are studied. Connected graphs which are edge geodetic self decomposable are characterized.

Induced label graphoidal graphs

Let G be a non-trivial, simple, finite, connected and undirected graph of order n and size m. An induced acyclic graphoidal decomposition (IAGD) of G is a collection ψ of non-trivial and internally disjoint induced paths in G such that each edge of G lies in exactly one path of ψ. For a labeling f : V → {1, 2, 3, . . . ,n}, let ↑ Gf be the directed graph obtained by orienting the edges uv of G from u to v, provided f(u) < f(v). If the set ψf of all maximal directed induced paths in ↑ Gf with directions ignored is an induced path decomposition of G, then f is called an induced graphoidal labeling of G and G is called an induced label graphoidal graph. The number ηil = min{|ψf| : f is an induced graphoidal labeling of G} is called the induced label graphoidal decomposition number of G. In this paper we introduce and study the concept of induced graphoidal labeling as an extension of graphoidal labeling.

Decomposition of Graphs into Paths and Cycles

A decomposition of a graph is a collection of edge-disjoint subgraphs of such that every edge of belongs to exactly one . If each is a path or a cycle in , then is called a path decomposition of . If each is a path in , then is called an acyclic path decomposition of . The minimum cardinality of a path decomposition (acyclic path decomposition) of is called the path decomposition number (acyclic path decomposition number) of and is denoted by () (()). In this paper we initiate a study of the parameter and determine the value of for some standard graphs. Further, we obtain some bounds for and characterize graphs attaining the bounds. We also prove that the difference between the parameters and can be made arbitrarily large.