In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may b...

where w(n) is an analysis window. At each time instant, the STFT is a discrete-time Fourier transform or discrete Fourier transform (DFT). Many DFT computing algorithms and architectures have been proposed. However, the direct use of the DFI' without considering the special sliding window effect of STFT is not an efficient approach. There are two major approaches for STFT. One is based on the f...

this paper considers the multi-depot vehicle routing problem with time window in which each vehicle starts from a depot and there is no need to return to its primary depot after serving customers. the mathematical model which is developed by new approach aims to minimizing the transportation cost including the travelled distance, the latest and the earliest arrival time penalties. furthermore, ...

This study aims to explore visual complexity in streetscape composition using RMS contrast information and Fractal Analysis. The dataset was composed of 74 streetscape images, taken in Algeria and Japan in daytime and nighttime. The evaluation and analysis covered two phases: (1) Subjective quantification of perceived complexity using ranking method. (2) Visual complexity measurement based on R...

The management of distributed software development projects presents many challenges. One of them happens right at the start of the project and consists of the allocation of tasks between remote teams. When allocating a task to a site, the project manager takes into account several factors such as technical knowledge of staff and proximity to the client. The project manager usually takes this d...

We discuss the advantages and disadvantages of a functional approach to clustering of spatial-temporal data. This leads us to suggest an alternative methodology which allows cluster memberships to vary over both temporal and spacial domains. One advantage of our approach is that it can easily incorporate time-varying covariates. A fitting algorithm is developed and we provide a simple simulatio...