In this paper, we consider a continuous description based on stochastic differential equations of the popular particle swarm optimization (PSO) process for solving global optimization problems and derive in the large particle limit the corresponding mean-field approximation based on Vlasov–Fokker–Planck-type equations. The disadvantage of memory effects induced by the need to store the local best position is overcome by the introduction of an additional differential equation describing the evolution of the local best. A regularization process for the global best permits to formally derive the respective mean-field description. Subsequently, in the small inertia limit, we compute the related macroscopic hydrodynamic equations that clarify the link with the recently introduced consensus based optimization (CBO) methods. Several numerical examples illustrate the mean field process, the small inertia limit and the potential of this general class of global optimization methods.
This paper investigates the influence of GSM speech coding on text independent speaker recognition performance. The three existing GSM speech coder standards were considered. The whole TIMIT database was passed through these coders, obtaining three transcoded databases. In a first experiment, it was found that the use of GSM coding degrades significantly the identification and verification performance (performance in correspondence with the perceptual speech quality of each coder). In a second experiment, the features for the speaker recognition system were calculated directly from the information available in the encoded bit stream. It was found that a low LPC order in GSM coding is responsible for most performance degradations. By extracting the features directly from the encoded bit-stream, we also managed to obtain a speaker recognition system equivalent in performance to the original one which decodes and reanalyzes speech before performing recognition.0-7803-6293-4/00/$10.00 02000 IEEE.
In this paper we present an efficient method for Content Based Image Retrieval (CBIR) of occluded images using DCT-phase. The proposed method utilizes a novel correlation metric for ternaryvalued DCT-phase, as well as a region merging method to reconstruct the non-occluded regions in the retrieved image. The proposed image retrieval method showed good performance when tested with different datasets containing reference images, occluded images, fused images and images with different JPEG compression ratios. Experimental evaluation also showed that the proposed image retrieval method performs better than current state of the art DCT-phase based image retrieval methods while retrieving not only occluded images but also reference images, fused images and images with different JPEG compression ratios.
In this paper we present SpikeOnChip, a custom embedded platform for neuronal activity recording and online analysis. The SpikeOnChip platform was developed in the context of automated drug testing and toxicology assessments on neural tissue made from human induced pluripotent stem cells. The system was developed with the following goals: to be small, autonomous and low power, to handle micro-electrode arrays with up to 256 electrodes, to reduce the amount of data generated from the recording, to be able to do computation during acquisition, and to be customizable. This led to the choice of a Field Programmable Gate Array System-On-Chip platform. This paper focuses on the embedded system for acquisition and processing with key features being the ability to record electrophysiological signals from multiple electrodes, detect biological activity on all channels online for recording, and do frequency domain spectral energy analysis online on all channels during acquisition. Development methodologies are also presented. The platform is finally illustrated in a concrete experiment with bicuculline being administered to grown human neural tissue through microfluidics, resulting in measurable effects in the spike recordings and activity. The presented platform provides a valuable new experimental instrument that can be further extended thanks to the programmable hardware and software.
Line Spectrum Pair (LSP) representation of Linear Predictive Coding (LPC) parameters is widely used in speech coding applications. An efficient method for LPC to LSP conversion is Kabal's method. In this method the LSPs are the roots of two polynomials P' p (x) and Q' p (x), and are found by a zero crossing search followed by successive bisections and interpolation. The precision of the obtained LSPs is higher than required by most applications, but the number of bisections cannot be decreased without compromising the zero crossing search. In this paper, it is shown that, in the case of 10 th -order LPC, five intervals containing each only one zero crossing of P' 10 (x) and one zero crossing of Q' 10 (x) can be calculated, avoiding the zero crossing search. This allows a trade-off between LSP precision and computational complexity resulting in considerable computational saving.
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