scholarly journals A Statistical Approach for Voiced Speech Detection

2011 ◽  
pp. 297-300
Author(s):  
Mihir Narayan Mohanty ◽  
Aurobinda Routray ◽  
Prithviraj Kabisatpathy
Keyword(s):  
Decision Rule ◽  
High Performance ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Ratio Test ◽  
Noisy Environments ◽  
Speech Detection ◽  
Voiced Speech ◽  
Variable Rate Speech Coding ◽  
Noise Statistics

Detection of Voice in speech signal is a challenging problem in developing high-performance systems used in noisy environments. In this paper, we present an efficient algorithm for robust voiced speech detection and for the application to variable-rate speech coding. The key idea of the algorithm is considering speech energy and zero crossings rate (ZCR) information simultaneously when processing speech signals and finding the end point of the signal. Next to it a decision rule and a background noise statistics estimator, by applying a statistical model. A robust decision rule is derived from the generalized likelihood ratio test (LRT) by assuming that the noise statistics are known a priori. The algorithm is most efficient for the time-varying noise. According to our simulation results, the proposed algorithm shows significantly better performance in low signal-to-noise ratio and in noisy environments.

scholarly journals Noise Estimation and Suppression Using Nonlinear Function withA PrioriSpeech Absence Probability in Speech Enhancement

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Soojeong Lee ◽  
Gangseong Lee
Keyword(s):  
Speech Enhancement ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Nonlinear Function ◽  
Noise Estimation ◽  
Noise Power ◽  
Sigmoid Function ◽  
Noisy Environments ◽  
Adaptive Parameter ◽  
Residual Noise

This paper proposes a noise-biased compensation of minimum statistics (MS) method using a nonlinear function anda priorispeech absence probability (SAP) for speech enhancement in highly nonstationary noisy environments. The MS method is a well-known technique for noise power estimation in nonstationary noisy environments; however, it tends to bias noise estimation below that of the true noise level. The proposed method is combined with an adaptive parameter based on a sigmoid function anda prioriSAP for residual noise reduction. Additionally, our method uses an autoparameter to control the trade-off between speech distortion and residual noise. We evaluate the estimation of noise power in highly nonstationary and varying noise environments. The improvement can be confirmed in terms of signal-to-noise ratio (SNR) and the Itakura-Saito Distortion Measure (ISDM).

scholarly journals Detection of Unresolved Targets for Wideband Monopulse Radar

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1084
Author(s):  
Tianyi Tsai ◽  
Zhiqiang Liao ◽  
Zhiquan Ding ◽  
Yuan Zhao ◽  
Bin Tang
Keyword(s):  
Target Detection ◽  
Detection Probability ◽  
High Performance ◽  
A Priori ◽  
Computation Time ◽  
Gaussian Mixture ◽  
Detection Algorithm ◽  
Ratio Test ◽  
Range Profile ◽  
Wideband Radar

Detecting unresolved targets is very important for radars in their target tracking phase. For wideband radars, the unresolved target detection algorithm should be fast and adaptive to different bandwidths. To meet the requirements, a detection algorithm for wideband monopulse radars is proposed, which can detect unresolved targets for each range profile sampling points. The algorithm introduces the Gaussian mixture model and uses a priori information to achieve high performance while keeping a low computational load, adaptive to different bandwidths. A comparison between the proposed algorithm and the latest unresolved target detection algorithm Joint Multiple Bin Processing Generalized Likelihood Ratio Test (JMBP GLRT) is carried out by simulation. On Rayleigh distributed echoes, the detection probability of the proposed algorithm is at most 0.5456 higher than the JMBP GLRT for different signal-to-noise ratios (SNRs), while the computation time of the proposed algorithm is no more than two 10,000ths of the JMBP GLRT computation time. On bimodal distributed echoes, the detection probability of the proposed algorithm is at most 0.7933 higher than the JMBP GLRT for different angular separations of two unresolved targets, while the computation time of the proposed algorithm is no more than one 10,000th of the JMBP GLRT computation time. To evaluate the performance of the proposed algorithm in a real wideband radar, an experiment on field test measured data was carried out, in which the proposed algorithm was compared with Blair GLRT. The results show that the proposed algorithm produces a higher detection probability and lower false alarm rate, and completes detections on a range profile within 0.22 ms.

scholarly journals Detection and localization of multiple small damages in beam

2021 ◽  
Vol 13 (1) ◽  
pp. 168781402098732
Author(s):  
Ayisha Nayyar ◽  
Ummul Baneen ◽  
Syed Abbas Zilqurnain Naqvi ◽  
Muhammad Ahsan
Keyword(s):  
Frequency Response ◽  
Natural Frequencies ◽  
Signal To Noise Ratio ◽  
Moving Average ◽  
A Priori ◽  
Damage Index ◽  
High Signal ◽  
Frequency Range ◽  
Spatial Locality ◽  
System Frequency

Localizing small damages often requires sensors be mounted in the proximity of damage to obtain high Signal-to-Noise Ratio in system frequency response to input excitation. The proximity requirement limits the applicability of existing schemes for low-severity damage detection as an estimate of damage location may not be known  a priori. In this work it is shown that spatial locality is not a fundamental impediment; multiple small damages can still be detected with high accuracy provided that the frequency range beyond the first five natural frequencies is utilized in the Frequency response functions (FRF) curvature method. The proposed method presented in this paper applies sensitivity analysis to systematically unearth frequency ranges capable of elevating damage index peak at correct damage locations. It is a baseline-free method that employs a smoothing polynomial to emulate reference curvatures for the undamaged structure. Numerical simulation of steel-beam shows that small multiple damages of severity as low as 5% can be reliably detected by including frequency range covering 5–10th natural frequencies. The efficacy of the scheme is also experimentally validated for the same beam. It is also found that a simple noise filtration scheme such as a Gaussian moving average filter can adequately remove false peaks from the damage index profile.

A High-Performance Signal Processing System for Monopulse Tracking Radar

2011 ◽  
Vol 383-390 ◽  
pp. 471-475
Author(s):  
Yong Bin Hong ◽  
Cheng Fa Xu ◽  
Mei Guo Gao ◽  
Li Zhi Zhao
Keyword(s):  
Signal Processing ◽  
High Performance ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Processing System ◽  
Digital Signal ◽  
Radar Signal ◽  
Signal Processing System ◽  
Parallel Pipelined ◽  
Tracking Radar

A radar signal processing system characterizing high instantaneous dynamic range and low system latency is designed based on a specifically developed signal processing platform. Instantaneous dynamic range loss is a critical problem when digital signal processing is performed on fixed-point FPGAs. In this paper, the problem is well resolved by increasing the wordlength according to signal-to-noise ratio (SNR) gain of the algorithms through the data path. The distinctive software structure featuring parallel pipelined processing and “data flow drive” reduces the system latency to one coherent processing interval (CPI), which significantly improves the maximum tracking angular velocity of the monopulse tracking radar. Additionally, some important electronic counter-countermeasures (ECCM) are incorporated into this signal processing system.

scholarly journals Automotive antenna diversity system for satellite radio with high phase accuracy in low SNR-scenarios

2018 ◽  
Vol 10 (5-6) ◽  
pp. 578-586 ◽  
Author(s):  
Simon Senega ◽  
Ali Nassar ◽  
Stefan Lindenmeier
Keyword(s):  
Signal To Noise Ratio ◽  
A Priori ◽  
Multipath Fading ◽  
Correction Method ◽  
Antenna System ◽  
Antenna Diversity ◽  
Phase Detection ◽  
Low Snr ◽  
Single Antenna ◽  
Noise Correction

AbstractFor a fast scan-phase satellite radio antenna diversity system a noise correction method is presented for a significant improvement of audio availability at low signal-to-noise ratio (SNR) conditions. An error analysis of the level and phase detection within the diversity system in the presence of noise leads to a correction method based on a priori knowledge of the system's noise floor. This method is described and applied in a hardware example of a satellite digital audio radio services antenna diversity circuit for fast fading conditions. Test drives, which have been performed in real fading scenarios, are described and results are analyzed statistically. Simulations of the scan-phase antenna diversity system show higher signal amplitudes and availabilities. Measurement results of dislocated antennas as well as of a diversity antenna set on a single mounting position are presented. A comparison of a diversity system with noise correction, the same system without noise correction, and a single antenna system with each other is performed. Using this new method in fast multipath fading driving scenarios underneath dense foliage with a low SNR of the antenna signals, a reduction in audio mute time by one order of magnitude compared with single antenna systems is achieved with the diversity system.

scholarly journals High-speed high-resolution laser diode-based photoacoustic microscopy for in vivo microvasculature imaging

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Xiufeng Li ◽  
Victor T C Tsang ◽  
Lei Kang ◽  
Yan Zhang ◽  
Terence T W Wong
Keyword(s):  
High Resolution ◽  
High Speed ◽  
High Performance ◽  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Cost Effective ◽  
High Signal ◽  
Photoacoustic Microscopy ◽  
Mouse Ear

AbstractLaser diodes (LDs) have been considered as cost-effective and compact excitation sources to overcome the requirement of costly and bulky pulsed laser sources that are commonly used in photoacoustic microscopy (PAM). However, the spatial resolution and/or imaging speed of previously reported LD-based PAM systems have not been optimized simultaneously. In this paper, we developed a high-speed and high-resolution LD-based PAM system using a continuous wave LD, operating at a pulsed mode, with a repetition rate of 30 kHz, as an excitation source. A hybrid scanning mechanism that synchronizes a one-dimensional galvanometer mirror and a two-dimensional motorized stage is applied to achieve a fast imaging capability without signal averaging due to the high signal-to-noise ratio. By optimizing the optical system, a high lateral resolution of 4.8 μm has been achieved. In vivo microvasculature imaging of a mouse ear has been demonstrated to show the high performance of our LD-based PAM system.

scholarly journals Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit

2015 ◽  
Vol 8 (11) ◽  
pp. 4817-4830 ◽  
Author(s):  
X. Xi ◽  
V. Natraj ◽  
R. L. Shia ◽  
M. Luo ◽  
Q. Zhang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Water Cycle ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Carbon Sources ◽  
Cost Effective ◽  
Accurate Estimation ◽  
Clear Sky ◽  
Notable Increase ◽  
Measurement Strategies

Abstract. The Geostationary Fourier Transform Spectrometer (GeoFTS) is designed to measure high-resolution spectra of reflected sunlight in three near-infrared bands centered around 0.76, 1.6, and 2.3 μm and to deliver simultaneous retrievals of column-averaged dry air mole fractions of CO2, CH4, CO, and H2O (denoted XCO2, XCH4, XCO, and XH2O, respectively) at different times of day over North America. In this study, we perform radiative transfer simulations over both clear-sky and all-sky scenes expected to be observed by GeoFTS and estimate the prospective performance of retrievals based on results from Bayesian error analysis and characterization. We find that, for simulated clear-sky retrievals, the average retrieval biases and single-measurement precisions are < 0.2 % for XCO2, XCH4, and XH2O, and < 2 % for XCO, when the a priori values have a bias of 3 % and an uncertainty of 3 %. In addition, an increase in the amount of aerosols and ice clouds leads to a notable increase in the retrieval biases and slight worsening of the retrieval precisions. Furthermore, retrieval precision is a strong function of signal-to-noise ratio and spectral resolution. This simulation study can help guide decisions on the design of the GeoFTS observing system, which can result in cost-effective measurement strategies while achieving satisfactory levels of retrieval precisions and biases. The simultaneous retrievals at different times of day will be important for more accurate estimation of carbon sources and sinks on fine spatiotemporal scales and for studies related to the atmospheric component of the water cycle.

scholarly journals АНАЛИЗ И ПРОГНОЗИРОВАНИЕ ЭФФЕКТИВНОСТИ ФИЛЬТРАЦИИ ОДНОМЕРНЫХ СИГНАЛОВ НА ОСНОВЕ ДИСКРЕТНОГО КОСИНУСНОГО ПРЕОБРАЗОВАНИЯ

2019 ◽  
pp. 19-29
Author(s):  
Сергей Клавдиевич Абрамов ◽  
Виктория Валерьевна Абрамова ◽  
Сергей Станиславович Кривенко ◽  
Владимир Васильевич Лукин
Keyword(s):  
Signal To Noise Ratio ◽  
A Priori ◽  
Statistical Parameter ◽  
Mean Square ◽  
Least Mean Square ◽  
Signal To Noise ◽  
Standard Size ◽  
Filter Parameter ◽  
Filtering Efficiency ◽  
Threshold Setting

The article deals with the analysis of the efficiency and expedience of applying filtering based on the discrete cosine transform (DCT) for one-dimensional signals distorted by white Gaussian noise with a known or a priori estimated variance. It is shown that efficiency varies in wide limits depending upon the input ratio of signal-to-noise and degree of processed signal complexity. It is offered a method for predicting filtering efficiency according to the traditional quantitative criteria as the ratio of mean square error to the variance of additive noise and improvement of the signal-to-noise ratio. Forecasting is performed based on dependences obtained by regression analysis. These dependencies can be described by simple functions of several types parameters of which are determined as the result of least mean square fitting. It is shown that for sufficiently accurate prediction, only one statistical parameter calculated in the DCT domain can be preliminarily evaluated (before filtering), and this parameter can be calculated in a relatively small number of non-overlapping or partially overlapping blocks of standard size (for example, 32 samples). It is analyzed the variations of efficiency criteria variations for a set of realizations; it is studied factors that influence prediction accuracy. It is demonstrated that it is possible to carry out the forecasting of filtering efficiency for several possible values of the DCT-filter parameter used for threshold setting and, then, to recommend the best value for practical use. An example of using such an adaptation procedure for the filter parameter setting for processing the ECG signal that has not been used in the determination of regression dependences is given. As a result of adaptation, the efficiency of filtering can be essentially increased – benefit can reach 0.5-1 dB. An advantage of the proposed procedures of adaptation and prediction is their universality – they can be applied for different types of signals and different ratios of signal-to-noise.

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