In BLAST (Bell-Laboratories LAyered Space Time) systems, multiple transmit and receive antennas are employed to achieve very high spectral efficiencies. The ideal detection method for such systems is the maximum-likel...
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In BLAST (Bell-Laboratories LAyered Space Time) systems, multiple transmit and receive antennas are employed to achieve very high spectral efficiencies. The ideal detection method for such systems is the maximum-likelihood (ML) algorithm. However, the ML complexity increases exponentially with the number of transmit antennas and the number of bits per modulation symbol. A reduced-complexity detection method has been suggested, using ordered successive interference cancellation. We consider two other suboptimum techniques: channel-based adaptive group detection and multistep reduced-constellation detection. The goal is to reduce the two aforementioned complexity exponentials. The algorithms efficiently combine linear processing with local ML search. We limit the complexity by maintaining small ML searching areas, while maximizing the performance under the complexity constraint by optimizing the front-end linear processing and the selection of the search areas.
This paper presents the endpoint detection approaches specifically for an isolated word uses Malay spoken speeches from Malaysian Parliamentary session. Currently, there are 7,995 vocabularies of utterances in the dat...
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This paper presents the endpoint detection approaches specifically for an isolated word uses Malay spoken speeches from Malaysian Parliamentary session. Currently, there are 7,995 vocabularies of utterances in the database collection and for the purpose of this study; the vocabulary is limited to ten words which are most frequently spoken selected from ten speakers. Endpoint detection, which aims to distinguish the speech and non-speech segments of digital speech signal, is considered as one of the key preprocessing steps in speech recognition system. Proper estimation of the start and end of the speech (versus silence or background noise) avoids the waste of speech recognition evaluations on preceding or ensuing silence. In this study, the endpoint detection and speech segmentation task is achieved by using the short-time energy (STE) and short-time zero crossing (STZC) measures and combination of both approaches. As a result, the Hidden Markov Model (HMM) recognizer derived the recognition accuracy rate of 91.4% for combination of both algorithms, if compared only 86.3% for STE and 82.1% for STZC rate alone. The experiments show that there are many problems arise where there are still misdetection of word boundaries for the words with weak fricative and nasal sounds. Other obstacles issues such as speaking styles or mood of speaking can also cause the recognition performance.
We analyze the effect of channel estimation errors on joint detection algorithms in TD-SCDMA system. We quantify how estimation errors affect the SNR in the receiver. We apply this analysis to the zero-forcing block l...
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ISBN:
(纸本)0780370104
We analyze the effect of channel estimation errors on joint detection algorithms in TD-SCDMA system. We quantify how estimation errors affect the SNR in the receiver. We apply this analysis to the zero-forcing block linear equalizer (ZF-BLE) joint detection algorithm. Theory and simulation results are consistent with each other.
Traditional risk identification methods often rely on manual inspections and post-event processing, which struggle to cope with the vast amounts of data and the real-time changes in the internet environment. Time seri...
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ISBN:
(数字)9798331533991
ISBN:
(纸本)9798331534004
Traditional risk identification methods often rely on manual inspections and post-event processing, which struggle to cope with the vast amounts of data and the real-time changes in the internet environment. Time series anomaly detection algorithms, as an effective data analysis tool, can identify abnormal changes in time series data. By utilizing spectral residual anomaly detection algorithms and sub-sequence anomaly detection algorithms, models were constructed to conduct an in-depth anomaly detection analysis of price data on the JD platform, providing a new solution for risk identification. The experimental results show that the precision, recall, and F1 scores of these two time series anomaly detection algorithms are significantly better than those of other comparative algorithms, demonstrating significant application value in risk identification.
A series of novel stack-based low-complexity algorithms are proposed for signal detection in V-BLAST wireless systems. Among them, basic stack (BST) algorithm achieves maximum-likelihood (ML) detection performance wit...
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A series of novel stack-based low-complexity algorithms are proposed for signal detection in V-BLAST wireless systems. Among them, basic stack (BST) algorithm achieves maximum-likelihood (ML) detection performance with tractable computation complexity. By optimizing BST algorithm through optimally ordering and adapting detection to channel matrix conditions, computation complexity and storage complexity are further reduced. An upper bound for average computation complexity of BST algorithm is derived analytically and it is shown that for a fixed channel matrix, upper-bound of average computation complexity of ML stack algorithm decreases exponentially as SNR increases. Simulation results show that stack-based algorithms achieve optimum performance with much lower average complexity than traditional ML detector.
The orthogonal frequency division multiplexing (OFDM) transmission technique applied in a multipath environment has a bit error rate (BER) comparable with a narrowband radio channel because the fading of each subcarri...
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The orthogonal frequency division multiplexing (OFDM) transmission technique applied in a multipath environment has a bit error rate (BER) comparable with a narrowband radio channel because the fading of each subcarrier is frequency-nonselective. To overcome this behavior and to reduce the BER a combination of OFDM and CDMA has been previously proposed. In this case the information bits are spread over many subcarriers. The present authors discuss the performance of OFDM-CDMA with BPSK or QPSK signalling over a frequency-selective Rayleigh fading channel. An important question is the detection strategy in an OFDM-CDMA system. The authors make a quantitative comparison of different detection algorithms: conventional correlation (equal gain, EGC), orthogonality restoring correlation (ORC), ORC with a threshold in order to suppress subcarriers with low signal strength (TORC) and an iterative improvement based on a maximum likelihood approach. With TORC and an optimal threshold a gain of more than 8 dB over conventional OFDM can be obtained at p/sub b/=10/sup -3/, if the fading of subcarriers is uncorrelated.
A comparison of the performance of three QRS detectors used in the analysis of electrocardiogram (ECG) during sleep is presented in this paper. Two widely used QRS detection algorithms based on digital filtering (DF) ...
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A comparison of the performance of three QRS detectors used in the analysis of electrocardiogram (ECG) during sleep is presented in this paper. Two widely used QRS detection algorithms based on digital filtering (DF) are compared with a newly introduced one, based on higher-order statistics (HOS). The percentage of QRS complexes failed detection along with the number of false positives and false negatives are measured for quantitative performance evaluation. Experimental results, when applying the proposed methods to nocturnal ECG recordings from the Sleep Laboratory of the Philipps University of Marburg, Germany, prove that the HOS-based QRS detector exhibits higher overall QRS detection accuracy (99.95%) than the two DF-based ones (99.75% and 99.59%, respectively). Moreover, it has lower noise susceptibility despite the presence of different noise types, such as smooth or abrupt baseline drift, 50 Hz powerline interference, electromyographic intervention or any arrhythmia effect due to sleep apnea.
Voice activity detection (VAD) algorithms have become an integral part of many of the standardized wireless cellular and personal communications systems (PCS). We present a comparative study of the performance of thre...
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Voice activity detection (VAD) algorithms have become an integral part of many of the standardized wireless cellular and personal communications systems (PCS). We present a comparative study of the performance of three proposed VAD algorithms under various acoustical background noise conditions. We also propose new ideas to enhance the performance of a VAD algorithm in wireless PCS speech applications.
Landmark extraction is used as the first step of many vision tasks such as tracking, image registration, localization, image matching and recognition. Furthermore, landmarks are used to reduce the data flow and conseq...
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Landmark extraction is used as the first step of many vision tasks such as tracking, image registration, localization, image matching and recognition. Furthermore, landmarks are used to reduce the data flow and consequently the computational costs. In this paper we extracted landmarks from echocardiography sequence, our algorithm is based on corner extraction, and then we evaluate our algorithm with applying some test. For this purpose, we evaluated the detectors according to their repeatability, stability and landmark localization under changes in noise.
The identification of DNA motifs remains an active challenge for the researchers in the bioinformatics domain. A considerable effort in this area was concentrated on understanding the evolution of the genome by identi...
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ISBN:
(纸本)9781467343572;1467343579
The identification of DNA motifs remains an active challenge for the researchers in the bioinformatics domain. A considerable effort in this area was concentrated on understanding the evolution of the genome by identifying the DNA binding sites for transcription factors. The evolution in genome sequencing has led to the appearance of numerous computational methods for finding the short DNA segments, known as motifs. In this study, we present some of the computational methods that exist and try to evaluate their performance in case of long sequences.
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