Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than th...Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than the elements themselves. These constraints follow generalized Kirchhoff＇s laws derived from physical constraints. Once we have a graph; then the working environment becomes the graph-theory. An algorithm derived from graph theory is developed within the paper in order to analyze general networks. The algorithm is based on computing all the spanning trees in the graph G with an associated weight. This weight is the product ofadmittance＇s of the edges forming the spanning tree. In the first phase this algorithm computes a depth first spanning tree together with its cotree. Both are used as parents for controlled generation of off-springs. The control is represented in selecting the off-springs that were not generated previously. While the generation of off-springs, is based on replacement of one or more tree edges by cycle edges corresponding to cotree edges. The algorithm can generate a frequency domain analysis of the network.展开更多
This paper presents the result of research of deep structure of natural language. The main result attained is the existence of a deterministic mathematical model that relates phonetics to associated mental images star...This paper presents the result of research of deep structure of natural language. The main result attained is the existence of a deterministic mathematical model that relates phonetics to associated mental images starting from the simplest linguistic units in agreement with the human response to different acoustic stimuli. Moreover, there exists two level hierarchy for natural language understanding. The first level uncovers the conceptual meaning of linguistic units, and hence forming a corresponding mental image. At the second level the operational meaning is found to suit, context, pragmatics, and world knowledge. This agrees with our knowledge about human cognition. The resulting model is parallel, hierarchical but still concise to explain the speed of natural language understanding.展开更多
文摘Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than the elements themselves. These constraints follow generalized Kirchhoff＇s laws derived from physical constraints. Once we have a graph; then the working environment becomes the graph-theory. An algorithm derived from graph theory is developed within the paper in order to analyze general networks. The algorithm is based on computing all the spanning trees in the graph G with an associated weight. This weight is the product ofadmittance＇s of the edges forming the spanning tree. In the first phase this algorithm computes a depth first spanning tree together with its cotree. Both are used as parents for controlled generation of off-springs. The control is represented in selecting the off-springs that were not generated previously. While the generation of off-springs, is based on replacement of one or more tree edges by cycle edges corresponding to cotree edges. The algorithm can generate a frequency domain analysis of the network.
文摘This paper presents the result of research of deep structure of natural language. The main result attained is the existence of a deterministic mathematical model that relates phonetics to associated mental images starting from the simplest linguistic units in agreement with the human response to different acoustic stimuli. Moreover, there exists two level hierarchy for natural language understanding. The first level uncovers the conceptual meaning of linguistic units, and hence forming a corresponding mental image. At the second level the operational meaning is found to suit, context, pragmatics, and world knowledge. This agrees with our knowledge about human cognition. The resulting model is parallel, hierarchical but still concise to explain the speed of natural language understanding.
