The optimization of feed forward neural networks structure using genetic algorithms.
The order of node removals in influence diagram
The performance profile: A multi-criteria performance evaluation method for test-based problems
In test-based problems, solutions produced by search algorithms are typically assessed using average outcomes of interactions with multiple tests. This aggregation leads to information loss, which can render different solutions apparently indifferent and hinder comparison of search algorithms. In this paper we introduce the performance profile, a generic, domain-independent, multi-criteria performance evaluation method that mitigates this problem by characterizing the performance of a solution by...
The present and future of signal processing
The quantitative evaluation of image quality and definition of an image
The relation of two patterns with comparable languages patterns
The star clustering algorithm for static and dynamic information organization.
The statistical interpretation and modification of GUHA method
The structural description of self-embedding nature of waveform peaks
The theory of function structure models.
The UD RLS algorithm for training feedforward neural networks
A new algorithm for training feedforward multilayer neural networks is proposed. It is based on recursive least squares procedures and U-D factorization, which is a well-known technique in filter theory. It will be shown that due to the U-D factorization method, our algorithm requires fewer computations than the classical RLS applied to feedforward multilayer neural network training.
The uncertainty measure of hierarchical quotient space structure.
The Value of Knowing that You Do Not Know
The value of knowing about data availability and system accessibility is analyzed through theoretical models of Information Economics. When a user places an inquiry for information, it is important for the user to learn whether the system is not accessible or the data is not available, rather than not have any response. In reality, various outcomes can be provided by the system: nothing will be displayed to the user (e.g., a traffic light that does not operate, a browser that keeps browsing, a telephone...
Theorem Provers for Substructural Logics
Theorem proving through depth-first test
Theorem-proving systems [Book]
Theoretical analysis of steady state genetic algorithms
Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are probabilistic algorithms for optimization, which mimic operators from natural selection and genetics. The paper analyses the convergence of the heuristic associated to a special type of Genetic Algorithm, namely the Steady State Genetic Algorithm (SSGA), considered as a discrete-time dynamical system non-generational model. Inspired by the Markov chain results in finite Evolutionary Algorithms, conditions are...
Theory of classification : a survey of some recent advances
The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.
Theory of Classification: a Survey of Some Recent Advances
The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.
Theory of types and data description