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Resolving radar signal ambiguities in digital radio frequency receivers using traditional identification (ID) techniques remains challenging. Parametric comparison of common received signal features such as radio frequency, pulse width, pulse repetition interval and angle-of-arrival can lead to either 1) multiple emitters producing a single ID, or 2) a single emitter producing multiple IDs. This work...
This paper develops an algorithm “Discrete Wavelet Transform with Adaptive Filter” (DWTAF) to transform Neutral speech into emotional speech like Angry, Happy or Sad and this is compared with two other emotion transformation algorithms. The other two algorithms are “Speech Transformation using Statistical Parameters and Pitch Contours” (STSPPC) and “Speech Transformation using Mel Frequency Cepstral...
A new method of classification of a speaker’s gender based on cumulant coefficients is proposed. The effect of an additive noise and measurement error of classification signs on accuracy of classification is analyzed. The expediency of construction of an adaptive system of classification operating with considering of masking of a speech signal by noise is shown. Comparison of the proposed method of...
The number of internet connected devices by all accounts is set to increase dramatically in coming years as Internet of Things technologies become cheaper and more convenient. Z-Wave devices have found application in building control, smart energy, health care and equipment monitoring. Its closed standard ensures interoperability of devices and this stability has led to its popularity among consumers...
Few research has been conducted on Uyghur speaker recognition. Among the limited works, researchers usually collect small speech databases and publish results based on their own private data. This ‘close-door evaluation’ makes most of the publications doubtable. This paper publishes an open and free speech database THUYG-20 SRE and a benchmark for Uyghur speaker recognition. The database is based...
Sound event recognition becomes a basic task in some applications. However, in low SNR condition, the accuracy rate is easily affected by the acoustic scene. To address the problem, this paper proposes a framework consisting of empirical mode decomposition (EMD), gray level co-occurrence matrix combined with higher-order singular value decomposition (GLCM-HOSVD), and random forests (RF). We use a...
In this paper, we demonstrate target classification using the proposed features in previously reported research under measurement uncertainty conditions. The MSTAR dataset is widely used real target measurements in automatic target recognition society. Extremely high classification results of the dataset, which are over 90% correct classification, have been reported from some literatures. However,...
The knowledge of a future throughput value for a user equipment (UE) in Long Term Evolution (LTE) or any other transmission technology is very valuable. It can be used in rate adaptation algorithms so that radio channel congestions may be mitigated thus allowing for better quality of experience of the wireless user. Such control usually would happen at the application layer so that the control loops...
We propose a novel blind polarization de-multiplexing for Stokes vector direct detection (SV-DD) to decrease DSP complexity while increase the spectral efficiency. Effectiveness of the algorithm is proven via a 40-Gb/s SV-DD over 160-km SSMF transmission.
A bidirectional blind equalization based on the constant modulus algorithm (CMA) and subspace-based algorithm (SBA) is proposed in this paper. Without any training sequence or channel estimation, blind equalization improves the transmission efficiency significantly in underwater acoustic communications. The combining scheme in which two outputs run in opposite directions exploits the diversity and...
Speaker recognition can be used as a security means to authenticate the speaker or as a forensic tool to determine who is likely to be the talker. For such critical applications, robustness or reliability of the system is crucial. In spite of the development and advancement in the field of speaker recognition, there are still many limitations and challenges. Amongst these, environment factors, in...
Beamforming (BF) with phased arrays is a critical and natural solution for millimeter-wave (mmWave) wireless communications due to the increased signal propagation attenuation. In this paper, we propose fast and efficient codebook-based BF training to estimate antenna weight vectors (AWVs) for next generation mmWave WLANs/WPANs or the fifth generation (5G) wireless systems with spatial multiplexing...
Blind detection of interference modulation order is studied in this paper. Exploiting the additivity property of cumulants for independent variables, we extend the techniques used in source automatic modulation classification to identify the interference modulation order. Using multi- class support vector machines, we show that accurate prediction performance can be achieved via supervised learning...
Conventional peak detection algorithms are not designed to include information on the expected peak shape. Therefore, commonly used detectors discard this valuable information and do not perform optimally in regard to the given possibilities. Designed and evaluated is a detector based on an artificial neural network, which is employed for pattern recognition in order to exploit the peak shape information...
Traditional works on time series classification usually use all of data in time series without distinction. However, that will swamp the discriminative information and decrease the correctness of classification. In this paper, a feature segment based time series classification algorithm was proposed, which only selects some highly discriminative time series data for classification. Firstly, an adaptive...
In uplink device-to-device (D2D) underlay cellular systems, massive multiple-input multiple-output (MIMO) seems promising as the large antenna array at the base station (BS) can nearly null the D2D-to- cellular interference. But the channel state information from all the users including D2D users to the BS is required to obtain the advantage. For the orthogonal channel training scheme, the pilot overhead...
In this paper, an adaptive multi-channel energy detector is presented for spectrum sensing applications. This method exploits the Empirical Mode Decomposition (EMD) and Cell-Averaging Constant False Alarm Rate (CA-CFAR) in an effort to maximize the probability of detection for a given probability of false alarm. First, the oversampled baseband signal is compared to its corresponding EMD noise-only...
The main objective of this work is to introduce two adaptive window-based notch detection techniques for Ultra Wideband (UWB) Frequency Coded (FC) chipless RFID system. The first proposed algorithm is the Window Based Singular Value Decomposition (WB-SVD), where various frequency dependent patterns of the notch are used as a training sequence for predefined bandwidth (window) to create an orthonormal...
Modern hearing aids often contain multiple microphones to enable the use of spatial filtering techniques for signal enhancement. To steer the spatial filtering algorithm it is necessary to localize sources of interest, which can be intelligently achieved using computational auditory scene analysis (CASA). In this article, we describe a CASA system using a binaural auditory processing model that has...
In this paper we propose an speaker verification approach by applying low-rank recovery approach under total variability space, which is trained by a modified Gaussian Mixture Modeling (MGMM) with the observation confidence. In this model, we construct UBM mean supervector by MGMM in order to train total variability matrix and obtain i-vectors. Besides, the low-rank recovery method is exploited to...
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