Abst rac t : We propose a parallel method for calculating the energy band structure. Our method can be easily implemented and does not require high speed of communication between the processors. In practical application our method allows for linear increase of the speed of calculations with the number of processors. We also analyse the optimization algorithms for energy band structure. We concl...

With the rapid development of swarm intelligence research field, a large number of algorithms in swarm intelligence are proposed one after another. The strong points and the drawbacks of a specific swarm intelligence algorithm becomes clear to be seen when the number of its application increases. To overcome the handicaps, some hybrid methods are invented. In this review, three hybrid swarm int...

This work has attempted to exploit information sharing to improve the results of Adaptive Simulated Annealing 1] as an optimization algorithm of the high-level synthesis of testable data paths. We have used Messengers 3] as a coordination tool to run several parallel instances of the annealing algorithm on the same design with diierent probability arrays for the perturbations. When all these in...

Efficient scheduling is of great significance to rationally make use of scarce satellite resources. Task clustering has been demonstrated to realize an effective strategy to improve the efficiency of satellite scheduling. However, the previous task clustering strategy is static. That is, it is integrated into the scheduling in a two-phase manner rather than in a dynamic fashion, without express...

A new algorithm is developed in this paper to support automatic name-face alignment for achieving more accurate cross-media news retrieval. We focus on extracting valuable information from large amounts of news images and their captions, where multi-level image-caption pairs are constructed for characterizing both significant names with higher salience and their cohesion with human faces extrac...

This paper presents a novel approach to the detection and recognition of qualitative parts like geons from real 2D intensity images. Previous works relied on semi-local properties of either line drawings or good region segmentation. Here, in the framework of Model-Based Opti-misation, whole geons or substantial sub-parts are recognised by tting parametric deformable contour models to the edge i...

We provide a new approach to stochastic optimization of smooth functions and give attention in particular to the optimization of superpositions of ridge functions.

We describe a real-time, internet-based S&P futures trading system, including a description of general aspects of internet-mediated interactions with electronic exchanges. Inner-shell stochastic nonlinear dynamic models are developed, and Canonical Momenta Indicators (CMI) are derived from a fitted Lagrangian used by outer-shell trading models dependent on these indicators. Recursive and adapti...

It is demonstr ated th at the chaotic properties of neural networks (in this case networks defined by the generalized delta procedur e) can be used to improve th eir learning performance. By adapt ively varying the learning-rate parameter an annealing mechanism can be introduced that is founded in chaos. T he prop osed mechanism, chaos-based learning, provides faster convergence than standard b...

Simulated annealing (SA) presents an optimization technique with several striking positive and negative features. Perhaps its most salient feature, statistically promising to deliver an optimal solution, in current practice is often spurned to use instead modified faster algorithms, “simulated quenching” (SQ). Using the author’s Adaptive Simulated Annealing (ASA) code, some examples are given w...