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An approach was developed using maximum eigenvalue principal components analysis(PCA) neural network for direct sequence spread spectrum (DSSS) signals to reconstruct the pseudo noise(PN) sequence blindly in low SNR conditions. Firstly, the received signals were divided into column vectors to form an observation matrix according to a temporal window, whose duration is one period of PN sequence. Then,...
Several theories of early sensory processing suggest that it whitens sensory stimuli. Here, we test three key predictions of the whitening theory using recordings from 152 ganglion cells in salamander retina responding to natural movies. We confirm the previous finding that firing rates of ganglion cells are less correlated compared to natural scenes, although significant correlations remain. We show...
This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based...
Kernel independent component analysis (KICA) detects primary independent components of data by minimizing kernelized canonical correlation of random variables in a reproducing kernel Hilbert space. KICA has been widely used in many practical tasks, e.g., blind source separation and speech recognition. However, the dense kernel matrix in traditional KICA causes high computational complexity which prohibits...
We present a tailored sparse principal component analysis approach to identify parts of the Hepatitis C virus (HCV) proteome that may be particularly susceptible to immune pressure and thus may help in the design of an effective vaccine. Considering the highly data-limited HCV NS5B protein, the proposed method reveals two reasonably small sets of potentially vulnerable sites which can serve as new...
Despite the phenomenal advances in the computational power of electronic systems, human-machine interaction has been largely limited to simple control panels, such as keyboards and mice, which only use physical senses. Consequently, these systems either rely critically on close human guidance or operate almost independently. A richer experience can be achieved if cognitive inputs are used in addition...
In this paper, computationally efficient subspace-based estimators with real-valued implementation are presented by introducing a preprocessing transformation to estimate carrier frequency offset (CFO) for interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. Conventional subspace-based estimators inevitably lead to intensive computational complexity due to calculating...
This paper presents some experimental results obtained for the diagnosis of the rotor broken bars in three identical squirrel cage induction generators by the analysis of stator current signatures MCSA using Periodogram, Covariance, and MUSIC techniques respectively. These signatures are detected from DSP of the test bench implemented at the laboratory.
To locate the position of the speaker, there are many methods, among of them, the method using steered response power is very popular. By phase transform, the steered response method (SRP-PHAT) is robust; with the noise increasing, the performance of the method becomes bad. Using principal eigenvector, the steered response power (SRP-PE) method is better than SRP-PHAT. In this paper, we propose an...
Counting the number of triangles in a large graph has many important applications in network analysis. Several frequently computed metrics such as the clustering coefficient and the transitivity ratio need to count the number of triangles. In this paper, we present a randomized framework for expressing and analyzing approximate triangle counting algorithms. We show that many existing approximate triangle...
The Direction of Arrival (DOA) algorithms can estimate the incident angles of all the received signals impinging on the array. These algorithms give the DOAs of all the relevant signals of the user sources and interference sources. However, they are not capable of distinguish and identify which one is the direction of the desired user. In this paper, we propose to use a reference signal which is known...
An ARMA (p, q) model parameterization method is proposed for approximating the Clarke's theoretical autocorrelation function. The MDL criterion is used for estimating the order of ARMA model on multipath Rayleigh fading. An ARMA (14, 13) model is obtained for approximating the Clarke's theoretical correlation by considering statistical parameter with the nominal of discrete-time and maximum Doppler...
Due to world economic situation, Electrical Distribution Utilities perform studies for automation and planning of distribution systems prioritizing their economic resources through projects related with technical, economic and social efficiency. During last years, Ecuadorian Electrical Sector has left aside determinant projects related with the efficiency, since there is not a good budget assignment...
In this paper, we propose a method to analyze epileptic electroencephalogram based on time series that is transformed from improved k-nearest neighbor network. The study of complex networks has become a hot research of electroencephalogram signal. Electroencephalogram time series generated by the network keeps node information of network, so researching the time series from the network can also achieve...
Sketch-based image retrieval (SBIR) has become a prominent research topic in recent years due to the proliferation of touch screens. The problem is however very challenging for that photos and sketches are inherently modeled in different modalities. Photos are accurate (colored and textured) depictions of the real-world, whereas sketches are highly abstract (black and white) renderings often drawn...
A novel algorithm is proposed for blind estimation of the spreading sequence in direct-sequence spread-spectrum (DSSS) communication systems. This algorithm is based on the maximum likelihood decision rule. Due to high computational complexity, the maximum likelihood method is feasible only for spreading sequence with very short periods. The novel algorithm has two steps for estimation. At first,...
We consider the remote estimation of a time-correlated field using an energy harvesting (EH) sensor. The sensor observes the unknown field and communicates its observations to a remote fusion center using an amplify-forward strategy. We consider the design of optimal transmission strategies in order to minimize the mean-square error (MSE) at the fusion center. Contrary to traditional approaches, the...
We investigate the problem of finding the real-valued vectors h, of size L, and x, of size P, from M independent measurements ym = 〈am, h〉〈bm, x〉, where am and bm are known random vectors. Recovery of the unknowns entails solving a set of bilinear equations, a challenging problem encountered in signal processing tasks such as blind deconvolution for channel equalization or image deblurring. Inspired...
The metric in the reproducing kernel Hilbert space (RKHS) is known to be given by the Gram matrix (which is also called the kernel matrix). It has been reported that the metric leads to a decorrelation of the kernelized input vector because its autocorrelation matrix can be approximated by the (down scaled) squared Gram matrix subject to some condition. In this paper, we derive a better metric (a...
Brain-computer interfacing (BCI) based on steady-state visual evoked potentials (SSVEPs) is one of the most practical BCIs because of its high recognition accuracies and little training of a user. Mixed frequency and phase coding which can implement a number of commands and achieve a high information transfer rate (ITR) has recently been gaining much attention. In order to implement mixed-coded SSVEP-BCI...
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