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Information hiding schemes using complete complementary codes (CCCs) have been developed for image data. It has been shown that a high payload and a low bit-error-rate (BER) can be achieved by such data hiding strategies because of the ideal correlation properties of CCCs. In this work, we apply a data hiding scheme based on CCCs to audio signals. Properties such as signal-to-noise ratio (SNR) and...
We present a data-driven method to analyze functional magnetic resonance imaging (fMRI) time-series where multiple hypotheses are generated for inferential methods from the data itself without any assumptions on the time-series. The method does not require the number of clusters to be defined a priori. Activation detection is based on region growing which specifically suits the spatiotemporal characteristics...
This paper proposes modification of previous audio zero-watermarking, proposed by Chen et. al [1], in terms of its watermark-key generation. We investigate that the size of previous watermark detection key is around two or three times larger than its watermark data. In order to yield an efficient key rather than generating three secret keys, we will exploit data indices, instead of field indices,...
In functional magnetic resonance imaging (fMRI) data, activated voxels are usually very small in number and are embedded in a mass of inactive voxels. For clustering analysis, this situation generates an ill-balanced data problem among different classes of voxels. In this paper we propose a novel method to overcome the ill-balanced data problem, by reducing the number of voxels to be processed by...
This paper introduces an implementation of a half-duplex decode-and-forward cooperative algorithm using the complete complementary code (CCC) sets. These code sets have an impulsive autocorrelation sum among each set and a cross correlation sum along the set size that vanishes for all shifts. Each user is assigned a set of spreading codes to spread his data and send each of the resulting signals on...
In functional magnetic resonance imaging (fMRI) data, activated voxels are usually very small in number and are embedded in a mass of inactive voxels. For clustering analysis, this situation generates an ill-balanced data problem among different classes of voxels. In this paper we propose a novel method to overcome the ill-balanced data problem by eliminating the inactive voxels prior to the application...
In this paper, a new beamformer is proposed for coherent signal reception with the assumption that the directions-of-arrival (DOA's) of the uncorrelated interferers are available. Here, the composite vector of the coherent sources is first estimated based on the use of a transformation matrix to eliminate the uncorrelated interferers. Then the optimum beamforming is performed based on the estimated...
This paper investigates the invariant detection problem of quadrature phase-shift keying (QPSK) direct sequence spread spectrum (DS-SS) signals in additive white Gaussian noise (AWGN). Using the complex Gaussian mixture signal model and invariance principle, we consider the constant-false-alarm-rate (CFAR) invariant detectors and other sub-optimal invariant tests, including the uniformly-most-powerful-invariant...
Ultra-wideband (UWB) communication systems are usually implemented by baseband spreading schemes relying either on time hopping (TH) or direct sequence (DS) codes. However these schemes are not suitable to cancel narrow band interference (NBI). Other approaches rely on digital single carrier spreading (SC) or multi-carrier (MC) spreading codes, offering flexibility in NBI cancellation.
The empirical mode decomposition (EMD) applied to analysis of nonstationary and nonlinear signals has attracted great research interests. In this paper, a novel adaptive approach based on EMD framework is introduced to remove noise from ultrawideband impulse radio (UWB-IR) signals. Specifically, the noisy UWB-IR signal is decomposed into a finite number of oscillatory modes known as intrinsic mode...
This paper considers power allocation in spatially-correlated dual-hop multiple-input multiple-output (MIMO) relay channels under power constraint for each hop channel. The proposed scheme allocates the transmit power considering the spatial correlation as well as the average signal-to-noise ratio (SNR) of dual-hop MIMO relay channels. By means of upper-bound analysis, the proposed scheme can minimize...
We propose a data hiding algorithm for stereo audio signals which embeds data using the polarity of the reverberations added to the high-frequency channels. We replace the high-frequency components with one middle channel, and embed data as the polarity of reverberations added to each channel in order to adjust the coherence between these channels. Blind detection of embedded data is possible using...
In this work, we consider the problem of centralized detection in wireless sensor networks when the sensors transmit coherently through a multiple access channel. We derive the optimal weighting at each sensor that maximizes the error exponent. Firstly, the noiseless case is considered and a closed form solution to the problem is found. Secondly, we generalize the formulation to consider additive...
In this paper, the original spatial correlation wavelet denoising has been improved and applied to analyze the data of terahertz time-domain spectroscopy (THz-TDS). The improved algorithm has introduced the conception of threshold coefficient and a suitable threshold to end iteration process of algorithm. Then introduce the scale discriminate coefficient and obtain the adaptive coefficient according...
Blind source extraction (BSE) may be an essential but a challenging task where multiple sources are convolved and/or time delayed. In this article we discuss the performance of multivariate calibration techniques that comprise of classical least square (CLS), inverse linear regression (ILS), principal component regression (PCR) and partial least square regression (PLS) in achieving this task in robust...
Aiming at the cyclostationary property of most communication signals, two cyclostationary algorithms are analyzed in detail, which are obtained by using the Lagrange multiplier method based on different combinations of optimization objectives and constraints, and a novel adaptive implementation method called forgetting factor method is proposed to improve the anti-jamming capability in weak signal...
Cognitive radio is a promising solution to the problem of spectrum scarcity by means of allowing secondary radio networks access the spectrum opportunistically. One of the most important issues in cognitive radio is how to detect existing over-the-air signals reliably. Not a few literatures have reported that signals could be detected via their inherent or embedded properties. However, these may not...
New, exact expressions for the bivariate Nakagami-q (Hoyt) processes with arbitrary correlation in a nonstationary environment are derived. More specifically, the following are obtained: joint probability density function, joint cumulative distribution function, power correlation coefficient, and some statistics related to the signal-to-noise ratio at the output of the selection combiner, namely,...
This paper presents a subband adaptive array (SBAA) with reduced pilot signal based on maximal ratio combining (MRC) scheme. By the subband processing, MRC design based on eigenfiltering which is widely used in frequency flat environments could be applied to frequency selective channels, but the efficient synthesis of output signal through the inverse DFT (discrete Fourier transform) is disturbed...
Matched filters are used when one would like to determine whether or not a particular, known waveform is present in a signal that has been corrupted by random noise. We show that in a sampled-data system, increasing the sampling rate only makes substantial improvements in the filter's performance up to a certain point. Sampling very quickly turns out to be a waste of effort. The justification of this...
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