This paper presents a method towards hierarchical symbolic analysis of linear analog circuits using twoport networks. The important difference to the ordinary flat symbolic analysis is, that we treat the transistor pairs as blocks and then derive the transfer function with network analyzer without to setup and solve a complicated DAE system for a whole analog circuit. The hierarchical idea can ...

The building blocks introduced earlier by us in [1] are used for constructing a hierarchical nonlinear model for nonlinear factor analysis. We call the resulting method hierarchical nonlinear factor analysis (HNFA). The variational Bayesian learning algorithm used in this method has a linear computational complexity, and it is able to infer the structure of the model in addition to estimating t...

In this paper we derive entropy bounds for hierarchical networks. More precisely, starting from a recently introduced measure to determine the topological entropy of non-hierarchical networks, we provide bounds for estimating the entropy of hierarchical graphs. Apart from bounds to estimate the entropy of a single hierarchical graph, we see that the derived bounds can also be used for character...

Multimedia data is now one of the widely used information types in all the fields as the fast development of computer techniques has been made traditional database systems based on text information have the limitations when applied to multimedia information. One of the main problems the researchers highlighted was the difficulty of locating a desired image in a large and varied collection. Whil...

Traditional multimedia indexing methods are based on the principle of hierarchical clustering of the data space where metric properties are used to build a tree that can then be used to prune branches while processing the queries. However, the performance of these methods will deteriorate rapidly when the dimensionality of the data space is increased. We describe a new hierarchical linear subsp...