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Developing a precise understanding of the dynamic behavior of time series is crucial for the success of forecasting techniques. We introduce a novel communication-theoretic framework for modeling and forecasting time series. In particular, the observed time series is modeled as the output of a noisy communication system with the input as the future values of time series. We use a data-driven probabilistic...
Noise is the key to cause phase measurement error of sine signals. Although there have been many attempts to suppress noise interference, high accuracy is still hard to meet in terrible noise environment. In order to improve reliability and accuracy of the measurement system, a robust method is proposed. In this paper, independent component analysis (ICA) is used to separate sine signal from noises...
In this paper, a noise robust formant frequency estimation scheme is developed utilizing the advantageous properties of the autocorrelation function of the band-limited noisy speech signal. It is shown that the use of autocorrelation operation on a speech signal, which is band-limited to a particular formant zone, in comparison to one without any band limitation, can provide higher noise immunity,...
As a multi-channel microwave remote sensing imaging radar system, polarimetric Synthetic Aperture Radar (SAR) enhances the information extraction ability for material scene in the observation area, in which the design and state monitoring for parameters play an important role in polarimetric SAR system and equipments management. This paper presents an analysis method for three typical polarimetric...
The precision of radar range measurements depends on certain conditions. For narrow band radar, it is well understood that signal bandwidth and random noise are essential for range resolution and accuracy. The things are more complicated for UWB radar since jitter, antenna behavior, and even the target itself will have influence. This article analyses some aspects distinguishing the UWB radar from...
One of the most important applications of digital signal processing (DSP) is wireless communication. This kind of application requires low power implementation of DSP, which generally uses fixed-point arithmetic. The fixed-point architectures should be developed to maintain the energy consumption power at a reasonable level. In this paper, an approach which adapts the fixed-point specification according...
Two effective ECG beat classification methods based on signal decomposition were compared in terms of effective feature selection and noise tolerance. The HOS-DWT-FFBNN method associated with the linear correlation based filter (LCBF) provides imposing capability to select the more representative features than the IC reordering method OWSL associated with the ICA-SVM method. Both methods are insensitive...
Position sensitive detector (PSD) is influenced by the background light source when the weak light falls on its photo sensitive face. This paper applies the technique of sine light intensity modulation and band-pass filter which can overcome the background light to enhance the signal to noise ratio (S/N) of this position detection system greatly. The sum-intensity signal and the difference-intensity...
Accurate endpoint detection is important for speech procession. The endpoint detection problem is nontrivial for non-stationary backgrounds where noises may be introduced by the speaker, the recording environment and the transmission system. In this paper, an effective endpoint detection algorithm is proposed for improving speech signal processing performance in noisy environment. The proposed speech/pause...
In the paper, an analysis of bistatic tracking accuracy in passive radar is presented. The influence of parameters such as integration time, probability of false alarm, signal-to-noise ratio and spectral density of process noise is investigated. Simulations are performed for three popular types of illuminators of opportunity: FM, DAB and DVB-T.
Noise suppression by linear filters for a time series is discussed. We propose a method for jointly estimating signal and noise correlation matrices by incorporating steering vectors of the noise or eigenvectors of the noise correlation matrix as well as steering vectors of the target signals. Our estimates bring us two significant advantages. One is reduction of computational cost in obtaining the...
In previous work we introduced a new missing data imputation method for ASR, dubbed sparse imputation. We showed that the method is capable of maintaining good recognition accuracies even at very low SNRs provided the number of mask estimation errors is sufficiently low. Especially at low SNRs, however, mask estimation is difficult and errors are unavoidable. In this paper, we try to reduce the impact...
The accuracy of the frequency estimation of a multifrequency signal component by Interpolated Discrete Fourier Transform (IpDFT) method is affected by systematic errors. In a Weighted Multipoint Interpolated Discrete Fourier Transform (WMIpDFT) method has been proposed in order to reduce these errors. This method uses only the rectangular and the 2-term maximum sidelobe decay windows. In this paper...
The paper presents one reduced-order Multi-Input-Multi-Output (MIMO) identification approach, Principal Hankel Component Algorithm (PHCA), for power system modal analysis and damping controller design. The PHCA method is modified, using finite pulse for signal excitation, and applied to the power system identification. The identification results show that it approximates the original system with tolerable...
Integrated navigation system of ALV is discussed in this paper, a data fusion method based on BP (back propagation) neural network is proposed for ALV's GPS/DR integrated navigation. System models have been established based on this data fusion method. Integrated navigation system uses GPS parameters as criterion to judge the validity of GPS. When GPS is valid, neural network is adopted for state...
State-of-the-art automatic speech recognition systems typically adopt the feature set containing mel-frequency cepstral coefficients (MFCC) and their time derivatives. The noise vulnerability of MFCC significantly degrades the recognition performance of such systems in noisy conditions. This paper describes a noise-robust feature extraction method. A set of new MFCC features is derived from the dynamic...
This paper presents a method based on classification techniques for automatic fault diagnosis of rolling element bearings. Experimental results achieved on vibration signals collected by an accelerometer on an experimental test rig show that the method can automatically detect different types of faults. Furthermore, the method is able, once trained on an appropriate representative set of basic faults,...
This paper addresses estimating the distance between wireless nodes using a two-way ranging technique that approaches the Cramer-Rao Lower Bound (CRB) on ranging accuracy in a white noise environment. Standard two-way ranging methods do not achieve this bound because sampling artifacts limit resolution through range binning, so multiple measurements are combined to improve performance. Code modulus...
Noise and signal-to-noise measurements are often made using sampled signals and discrete Fourier transforms. In addition to the sampling and circular spectrum issues associated with making an accurate measurement, it is important to understand how accurate and repeatable the measurement is. This work provides an analysis of the expected accuracy of a spectral noise measurement and a method to determine...
Based on the "half stock fence"-interpolated FFT coefficients of a single-tone sequence, this paper presents a novel frequency estimation iteration algorithm starting with the Rife-Jane's estimator, which develops a symmetry frequency offset estimator and employs adaptive adjustment technique of the symmetric center. Computer Monte-Carlo simulations show that the algorithm is effective and...
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