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In this paper, an improved nonnegative matrix factorization (NMF) algorithm is proposed for single channel blind source separation and applied to speech enhancement. By adding time correlation item to objective function to constrain the time-varying gain coefficients of noise, it can achieve better effect of speech enhancement. We propose an efficient algorithm to optimize objective function with...
The field of side-channel analysis has made significant progress over time. Side-channel analysis is now used in practice in design companies as well as in test laboratories, and the security of products against side-channel attacks has significantly improved. However, there are still some remaining issues to be solved for side-channel analysis to become more effective. Side-channel analysis consists...
Our aim is to investigate long range predictions (up to several wavelengths) of the small-scale fading of radio channels. The purpose is to enable advanced 5G downlink transmission schemes that require accurate channel state information at transmitters, such as massive MIMO and coherent joint transmission, for vehicular users.
We present a holistic segmentation-free query by example word spotting technique based on template matching. We have applied this technique to a dataset of historical Arabic handwritten manuscript images. First, the documents as well as query word images are pre-processed for separating text from the noisy background and converting to their binary equivalents. Then a pixel based approach is used for...
For ultrasonic echo signals, to analyze the maximum peak ± 1 period error in the cross-correlation measurement of the finite sequence, to propose a method to increase the ratio of the maximum peak and the adjacent peak, and to avoid the periodic deviations in the maximum cross-correlation peaks. This method uses a dual-frequency excitation signal and a selective envelope with a triangular fast decay...
Speech enhancement using adaptive filtering methods are known to give good signal recovery from the noisy speech signal. Among these, Least Mean Square (LMS) and Recursive Least Squares (RLS) algorithms are more popular. These algorithms have a constraint that correlating noise should be given as the reference signal for denoising. Therefore in all the adaptive algorithms, two microphones are used,...
User-generated trajectories (UGT), such as GPS footprints from wearable devices or travel records from bus companies, capture rich information of human mobility and urban dynamics in the offline world. In this paper, our objective is to enrich these raw footprints and discover the users' personal interests by utilizing the semantic information contained in the spatial-and temporal-aware user-generated...
Direct Sequence Spread Spectrum (DSSS) signal has been widely used because of its low signal-to-noise ratio, strong anti-interference, low interception rate and multi-path effect. It is gradually replacing the traditional communications, and widely used in modern military and commercial communications systems. Therefore, the corresponding direct-communication communication reconnaissance technology...
This paper presents a demo proposal of a standalone smartphone application that can automatically analyse the signal quality of PCG, as it is recorded on a low-cost smartphonebased digital stethoscope. Features, related to the inherent pattern of the autocorrelated signal envelope, have been used for classifying and discarding the noisy portions from a continuous PCG. Our application has been successfully...
The Wiener filter is a well-known signal processing method for improving a noisy signal's quality. The Wiener filter requires either knowledge of or estimates of the power spectra of the signal-of-interest and of the undesired noise, leading to implementation challenges. In this paper, we show how a recently-developed second-order signal quantity termed the panorama can be employed to compute the...
Real-world visual classification tasks typically need to deal with data observed from different domains. Inspired by canonical correlation analysis (CCA), we propose an enhanced CCA with local density for associating and recognizing cross-domain data. In addition to maximizing the correlation of the projected cross-domain data, our CCA model further exploits the local density information observed...
Magnitude-only resting-state fMRI data have been largely investigated via independent component analysis (ICA) for exacting spatial maps (SMs) and time courses. However, the native complex-valued fMRI data have rarely been studied. Motivated by the significant improvements achieved by ICA of complex-valued task fMRI data than magnitude-only task fMRI data, we present an efficient method for de-noising...
In many practical transcoding applications, such as video surveillance, the source videos are often contaminated by noise. The presence of noise not only results in poor compression efficiency and visual quality, but also imposes an adverse effect on the performance of subsequent video analysis tasks. Thereby it is very necessary to denoise the video. In this paper, we propose an efficient mode decision...
This paper deals with the problem of single-channel noise reduction. Thanks to the eigenvalue decomposition, we arrange the eigenvalues of the speech correlation matrix in such a way that all the spectral mode signal-to-noise ratios (SNRs) of the noisy speech are ordered in a descending manner. By maintaining no speech distortion in the spectral modes with high input SNRs while allowing some degree...
Automatic adjustment of the hearing aid according to the intelligibility for the user in the environment could be beneficial. While most intelligibility metrics require a clean speech reference, i.e. intrusive methods, this is rarely available in real-life. This paper proposes a non-intrusive intelligibility metric in which a reconstruction of the clean speech is used in the established intrusive...
In stereo or multi-channel system identification, the most critical problems regarding online identification, e.g., for acoustic echo control, are the correlation properties of the excitation signals of the different audio channels. In this paper the impact of both the auto- and cross-correlation properties is considered and investigated. A new system combining appropriate decorrelation techniques...
In the scientific research and engineering practice, the detection of weak signal is often encountered. The traditional signal detection method can not accurately and effectively analyze the weak current. To this end, a phase-locked amplification was proposed to detect weak signal. According to the relevant theory of phase-locked amplifier, using the characteristic that the correlation between the...
The paper deals with the estimation of the noise covariance matrices of a linear time-varying system described by the state-space model. In particular, the stress is laid on the correlation methods and a novel method, the measurement difference autocovariance method, is proposed. The proposed method is based on the statistical analysis of differenced linearly transformed and shifted measurements resulting...
Because of the challenge of collecting labelled training data, zero-shot learning (ZSL) which transfers semantic knowledge represented by category attributes from seen classes to recognize unseen classes has received a lot of attention recently. Existing methods assume that the source attributes are completely correct in zero-shot learning. However, the source attributes in practice may contain noise...
Noise is omnipresent in almost all acoustical environments. The investigation presents here seeks to quantify the impact of noise on mel-frequency cepstral coefficients (MFCC) of speech signal. MFCC is one of the most commonly used features for speech recognition systems. However, it has been observed that performance of MFCC based system degrades drastically with changing noise levels and noise types...
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