In this paper, we investigate the problem of the computation of the posterior Cramer-Rao bound (PCRB) in the context of bearings-only tracking (BOT) for a manoeuvring target. The PCRB provides a lower bound on the mea...
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(纸本)1424409535
In this paper, we investigate the problem of the computation of the posterior Cramer-Rao bound (PCRB) in the context of bearings-only tracking (BOT) for a manoeuvring target. The PCRB provides a lower bound on the mean square error. In a recent paper, Hernandez et al have proposed a new approach named best-fitting Gaussian (BFG) model to calculate the bound for jump Markov linear filtering problems with a linear measurement equation. Thanks to the linear property of the measurement equation, an exact formula for the PCRB associated to the BFG model can be obtained via a classical Riccati-like recursion. However, in the BOT framework, the measurement equation is non linear so that we do not have a closed-form formula. Consequently, the BFG-PCRB must be approximated using Monte-Carlo methods. This implies a high computational burden. We show in this paper that the BFG model associated to the BOT problem can be computed exactly using another coordinate system named log polar coordinate (LPC) system
A new MPEG-4 standard for lossless audio coding is going to be published in 2006. This coming international standard consists of two parts: the transform-domain scalable to lossless coding (SLS), and the time-domain a...
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A new MPEG-4 standard for lossless audio coding is going to be published in 2006. This coming international standard consists of two parts: the transform-domain scalable to lossless coding (SLS), and the time-domain audio lossless coding (ALS). In ALS, linear prediction is used to compress the dynamic ranges of the input audio signal. The prediction residual is coded by an entropy coder with either Rice code or arithmetic code. There are two prediction modes in ALS: linear predictive coding (LPC) and cascaded RLS-LMS. As the developer of the RLS-LMS prediction, we present this technology in this paper. In RLS-LMS prediction, the input audio samples go through the cascaded DPCM, RLS, and LMS predictors, whose output predictions are linearly combined to generate a prediction for the current input sample. Through MPLG testings, it has been found that ALS with RLS-LMS prediction provides the best lossless compression ratio compared with SLS, ALS with LPC, and several non-MPEG codecs
Most of low bit-rate speech coders based on the speech production model use line spectrum frequencies (LSFs) to represent short-term spectra of speech signals. A vector predictor for the LSFs which consists of a group...
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Most of low bit-rate speech coders based on the speech production model use line spectrum frequencies (LSFs) to represent short-term spectra of speech signals. A vector predictor for the LSFs which consists of a group of grey predictors is investigated in this paper for the purpose of estimating the current LSFs accurately by using previous LSFs. We impose a new parameter called fractional step (FS) on the grey predictor which is determined by the steepest descent method in achieving the optimal prediction performance. Furthermore, the vector predictor can easily be applied to a vector predictive coder for spectral quantization. The experimental results show that the direct scalar quantization and partitioned vector quantization for the LSFs need, in total, 34 bits/frame and 27 bits/frame, respectively to achieve the spectral distortion limen (DL) of 1 dB. The proposed vector predictor with scalar quantization scheme can maintain the same spectral distortion at only 24 bits/frame.
With the increasing use of audio sensors in surveillance and monitoring applications, event detection using audio streams has emerged as an important research problem. This paper presents a hierarchical approach for a...
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With the increasing use of audio sensors in surveillance and monitoring applications, event detection using audio streams has emerged as an important research problem. This paper presents a hierarchical approach for audio based event detection for surveillance. The proposed approach first classifies a given audio frame into vocal and nonvocal events, and then performs further classification into normal and excited events. We model the events using a Gaussian mixture model and optimize the parameters for four different audio features ZCR, LPC, LPCC and LFCC. Experiments have been performed to evaluate the effectiveness of the features for detecting various normal and the excited state human activities. The results show that the proposed top-down event detection approach works significantly better than the single level approach
The authors present a new speech processing software designed for clinical observation of vocal disorders, speech assessments and some pathologies identification. By using a recorded speech sound of a patient, they us...
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The authors present a new speech processing software designed for clinical observation of vocal disorders, speech assessments and some pathologies identification. By using a recorded speech sound of a patient, they use a PDA algorithm implemented under Matlab in order to extract the vocal parameters (pitch period, formant frequencies, jitter, shimmer). The obtained results are compared with the normal values in order to an eventual disorder classification, a pathological prediction and prostheses assessments
As most of the researches on speech recognition (SR) are based on hidden Markov models (HMM), the main theme of this paper is the recognition of Arabic sounds using artificial neural networks. Despite the fact that Ar...
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As most of the researches on speech recognition (SR) are based on hidden Markov models (HMM), the main theme of this paper is the recognition of Arabic sounds using artificial neural networks. Despite the fact that Arabic is a language that is spoken by millions of people, and it is the sixth (K. Kirchhoff and J. Bilmes, 2002) spoken language in the world, we have faced a scarcity of researches in Arabic language recognition during the preparation of this paper. Speech recognition systems will become more used as they started to replace some of the functions normally accomplished with a keyboard, these and many other reasons encouraged us to continue in this field
To use distribution networks effectively and ensure the smooth introduction of distributed generations, we proposed a loop or mesh structure for distribution systems using a loop power flow controller (LPC) at the ope...
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To use distribution networks effectively and ensure the smooth introduction of distributed generations, we proposed a loop or mesh structure for distribution systems using a loop power flow controller (LPC) at the opened switch that can connect the adjoining feeder. A LPC offers optimal control for distribution systems from the viewpoints of reducing voltage rise, voltage fluctuation and loss minimum power flow control, and so on, having first ascertained the state of the distribution systems. To adapt to areas that cannot use communication systems, from the viewpoints of power quality for the transition phenomena, we also required distributed control using local voltage information for the LPC control. The purposes of this paper are to show power flow and reactive power control for a LPC, and propose a method of determining control coefficients using the optimal operation pattern of LPC and local voltage information. The distributed control using these control coefficients was verified by a 6.6 kV 100 kVA BTB (back to back) type LPC and distribution system testing facility at CRIEPI
The new telecommunications services have been pushing toward the development of improvements in speech coding, because of the need to improve encoded speech quality, using the lowest transmission rate possible. This s...
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The new telecommunications services have been pushing toward the development of improvements in speech coding, because of the need to improve encoded speech quality, using the lowest transmission rate possible. This study analyzes and proposes a method to adjust LSF parameters in order to improve their accuracy, minimizing the losses in the encoded LSFs interpolation process. With this scheme, the synthesized speech perceptual quality at the decoder end is increased, without relying on an increase of the transmission rate. We present a mathematical optimization method that minimizes different distortion measures, namely the Euclidean distortion measure and an approximation of the spectral distance in a detailed way. To evaluate the performance of the proposed improvements, the method is implemented in a speech coder with average rates below 2 kb/s. The results confirm that it is possible to obtain significant reduction in distortion measures using the proposed adjustment method of LSFs.
A novel method of pitch detection, combining LPCbased Cepstrum and Harmonic Product Spectrum (HPS), has been proposed. The interaction between the vocal tract and the glottal excitation disturb the detection from glot...
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A novel method of pitch detection, combining LPCbased Cepstrum and Harmonic Product Spectrum (HPS), has been proposed. The interaction between the vocal tract and the glottal excitation disturb the detection from glottal excitation, so we use linear Prediction Residual to eliminate the vocal tract information and the high frequency noise which can improve the accurate to some extent. In real world, when the speech signal has been transmitted through the telephone system, low frequency including pitch information have been cut off which can significantly attenuate the detection of fundamental pitch frequency. In this paper, we use the novel method combining LPC-based Cepstrum and HPS to deal with this problem and pitch errors. Experiment studied indicates that this novel method is effective and valuable for application in pitch detection, since it robustly handles different frequency domain noise and pitch errors.
We introduce an efficient algorithm for real-time compression of temporally consistent dynamic 3D meshes. The algorithm uses mesh connectivity to determine the order of compression of vertex locations within a frame. ...
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We introduce an efficient algorithm for real-time compression of temporally consistent dynamic 3D meshes. The algorithm uses mesh connectivity to determine the order of compression of vertex locations within a frame. Compression is performed in a frame to frame fashion using only the last decoded frame and the partly decoded current frame for prediction. Following the predictivecoding paradigm, local temporal and local spatial dependencies between vertex locations are exploited. In this framework we present a novel angle preserving predictor and evaluate its performance against other state of the art predictors. It is shown that the proposed algorithm improves up to 25% upon the current state of the art for compression of temporally consistent dynamic 3D meshes.
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