The main purpose of this study is to evaluate the computational efficiency of algorithms for calculating shortest paths when they are correctly coded by using the C programming language. This paper thoroughly measures the benefit of using the C programming language for coding shortest path algorithms. For each algorithm, we suggest computer implementation that take full advantage of the pointer...

This paper studies computational efficiency of suboptimal Model Predictive Control (MPC) with neural models. The algorithm requires solving on-line only a quadratic optimisation problem. Considering a nonlinear polymerisation process, for which the linear MPC algorithm is inadequate, it is shown that the suboptimal algorithm results in closedloop control performance similar to that obtained in ...

It is well-known that neural networks are computationally hard to train. On the other hand, in practice, modern day neural networks are trained efficiently using SGD and a variety of tricks that include different activation functions (e.g. ReLU), over-specification (i.e., train networks which are larger than needed), and regularization. In this paper we revisit the computational complexity of t...

In this correspondence, a simple design method for multirate near perfect reconstruction (NPR) integer decimated filter bank with non-uniform frequency spacing and linear phase property, that involves optimization of only single parameter, is proposed. It is derived from the uniform cosine modulated filter bank (CMFB) by merging some relevant band pass filters. The design procedure and the stru...

In Electronic Commerce, the intra-organizational coordination of directly responsible units, e. g. profitcenters or firms within an affiliated group, is of increasing importance. These organizational units can be modeled within a Multi-Agent System (MAS), an interconnection of autonomous information systems. This paper investigates co-ordination mechanisms for MAS in decentralized transportatio...

This paper analyses the strengths and weaknesses of some of the most popular traditional and contemporary 3D vision techniques for accuracy, robustness and computational efficiency. A novel technique is proposed that extends traditional stereo vision algorithms using some of the previously identified techniques resulting in improved robustness, accuracy and computational efficiency. The new mul...

The use of synthetic self-similar traffic in computer networks simulation is of vital importance for the capturing and reproducing of actual Internet data traffic behavior. A commonly used technique for generating selfsimilar traffic is achieved by aggregating On/Off sources where the active (On) and idle (Off) periods exhibit heavy tailed distributions. This work analyzes the balance between a...

Simulation smoothing involves drawing state variables (or innovations) in discrete time state-space models from their conditional distribution given parameters and observations. Gaussian simulation smoothing is of particular interest, not only for the direct analysis of Gaussian linear models, but also for the indirect analysis of more general models. Several methods for Gaussian simulation smo...

Most transformational linguists would no longer create explicit deep structures. Instead they adopt a surface-tnterpretlve approach. We find deep structures indIspensable for projection into a semantic network. In conjunction wrth a reference architecture based on constraint-posting, they mlnlmlze referential non-determinism% We extend Marcus’ Determm~sm Hypothesis to include rmmed/ate referenc...

Models encountered in computational physics and engineering, in particular computational mechanics, usually involve too many degrees of freedom, too many simulation time-steps, too many iterations (non-linear models, optimization or inverse identification), too many particles (in atomistic descriptions) or simply excessive simulation time (for example when simulation in real time is envisaged)....