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The maximum likelihood (ML) estimation for multipath component (MPC) parameters requires high computational complexity, resulting in low efficiency in channel measurement campaigns. In this paper, a new method, called Fast Reduced-Dimension SAGE (FRDS) algorithm, is proposed to estimate the parameters such as excess delay, power, and angle-of-arrival/departure (AoA/AoD). By sounding channels using...
Multiview canonical correlation analysis (MCCA) is an effective tool for analyzing the relationships among group- aligned multidimensional samples, which has been applied to the fields of pattern recognition and computer vision. In MCCA, its first-stage canonical variables are solved by a multivariate eigenvalue problem that can be computed by Horst method. However, how to use the algorithm for effectively...
To date, the basis of eigenvector spatial filtering is solely the centered spatial weights matrix (SWM) that is part of the Moran Coefficient (MC). The Laplacian matrix, < CI >diag-C offers an alternative transformation of the SWM, one associated with the Geary Ratio (GR), another popular measure of spatial autocorrelation (SA). This paper compares these two specifications, respectively denoted...
Multiple view data with different feature representations have widely arisen in various practical applications. Due to the information diversity, fusing multiview features is very valuable for classification purpose. In this paper, we propose a new multifeature fusion method called fractional-order discriminative multiview correlation projection (FDMCP), which is based on fractional-order scatter...
A general analytical framework based on generalized mutual information is applied to the analysis of massive multiple-input-multiple-output systems with low-resolution output quantization. For Gaussian codebook ensemble and nearestneighbor decoding rule, an equivalence relationship is established for general nonlinear transceiver distortion, that the effective signal-to-noise ratio based on the generalized...
The change of the vibration signal can reflect the mechanical state of the HV circuit breaker. An efficient method of feature extraction of the vibration signal usually pays a key role in the validity of the fault diagnosis and also lays the foundation for the fault classification in the subsequent stage. The paper presented a feature extraction method which is based on average empirical mode decomposition...
In this paper, we present a novel pseudo sequence based 2-D hierarchical reference structure for light-field image compression. In the proposed scheme, we first decompose the light-field image into multiple views and organize them into a 2-D coding structure according to the spatial coordinates of the corresponding microlens. Then we mainly develop three technologies to optimize the 2-D coding structure...
In speech enhancement algorithm based on generalized sidelobe canceller (GSC), when there is error in direction estimating, the target speech will not be blocked by blocking matrix (BM) module completely. Then in the later multiple-input canceller (MC) module, the target speech will be eliminated, which will cause the leakage of the target speech. In this paper, a new optimization algorithm is proposed...
Recently, steganalysis based on hypothesis test theory becomes a focus. However, the correlation between adjacent pixels is not exploited and this is obviously not reasonable. In this paper, a new detector for least significant bit matching (LSBM) steganography is proposed with the consideration of pixel correlation. The cover pixels are modeled by multivariate Gaussian distribution and a new detector...
For many data mining and machine learning tasks, the quality of a similarity measure is the key for their performance. To automatically find a good similarity measure from datasets, metric learning and similarity learning are proposed and studied extensively. Metric learning will learn a Mahalanobis distance based on positive semi-definite (PSD) matrix, to measure the distances between objectives,...
Based on a ring, a disk and an elliptical scattering models, the power spectrum densities (PSDs) are derived and investigated for fixed-to-fixed (F2F) propagation scenarios where a local scatterer is moving in any direction with random velocity at the predefined geometries of the models. The velocity distributions of the scatterers are assumed to follow uniform, exponential and mixed Gaussian, and...
Recently, some statistically optimal steganalyzers are proposed based on hypothesis testing theory, in which the cover pixels are supposed to be independent. However, the independent assumption is of limited interest since redundancy exists in natural images. In this paper, using a more appropriate image model considering pixel correlation, a new steganaly-sis method for the least significant bit...
Fractional-pel motion compensation is very good at improving video coding efficiency, especially for camera-captured content. But for screen content, which is obtained from a computer desktop, motion vectors with integer-precision may be enough to represent the motion in different pictures. Using fractional-pel motion compensation for such content is a waste of bits. Thus, adaptive motion compensation...
Chaos-based dynamics system is typical of the properties of randomness, determinacy and sensitivity to the initial parameters, which makes it suitable for the application of image encryption. In this paper, a wavelet domain color image encryption algorithm based on chaos is proposed. The color plain image is firstly decomposed into R, G, B components. Then an improved 3D chaotic cat map is proposed...
Direct spread spectrum signal with high anti-interference property, It has the characteristics of pseudo noise. Research on direct spread spectrum signal parameter estimation has important practical significance. According to the transmission characteristics of direct spread spectrum signal, using the time domain correlation method to estimate pn code period and using the frequency domain smooth periodogram...
In this paper, computational verb correlation (verb correlation, for short) is applied to stock market in order to find the correlation between different stock indexes. In previous works, computational verb similarities are used to provide the measurement for selecting the attributes in order to train decision trees. In this paper, a training method of decision tree is constructed based on verb correlation...
Cooperative Coevolutionary Evolutionary Algorithm is an extension of conventional Evolutionary Algorithm: it implements the idea of divide and conquer by dividing the whole set of variables into several subsets (groups), and evolve each subset independently with a certain optimizer. How to group the variables effectively have been studied by several researchers. Quite a number of variable grouping...
Cross-domain collaborative filtering (CF) is an emerging research topic in recommender systems. It aims to alleviate the sparsity problem in individual CF domains by transferring knowledge among related domains. In this paper, we will give a brief survey of the pilot studies in this research line in two dimensions: Collaborative Filtering Domains and Knowledge Transfer Styles. Some possible extensions...
Spectrum Sensing is the first challenge of Cognitive Radio. The signal detection of primary users (PU) is a basic premise of spectrum sensing. In this paper, we adopt a method based on the sample autocorrelation of received signal to detect the existence of primary users' signals. It is called Sample Autocorrelation Matrix (SAM) method. Simulation results by using the randomly the captured digital...
The article takes C2C online shopping pattern as the background of customer loyalty research, drawing on relevant theoretical research results and combines with the characteristics of C2C online shopping mode, and then comes up with three factors that affect customer loyalty and the theoretical model, bringing forward relevant assumptions. Through questionnaire design, questionnaire survey and sample...
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