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Chinese informal finance has shown its own characteristics and scale of development. Based on empirical data of Wuhan city which is the metropolis in the central and western region of China, the author attempts to explore the objective laws of the development of informal finance in developing countries such as China. This paper has described the various characteristics of informal finance in Wuhan,...
This paper proposed the thermo-economics evaluation system of cogeneration according to its characteristics. Base on the proposed evaluation method, the relative weight of indexes at all levels are analyzed. Using the AHP and expert estimation method, the thermo-economics of a combined heat and power unit in Ningxia province was evaluated. The method proposed in this paper provides integrated indexes...
The present work developed a basis to explore numerous damage events utilizing Self-Organizing Map (SOM) introducing Kullback-Leibler (KL) divergence as an appropriate similarity for frequency spectra of damage events. Firstly, we validated the use of KL divergence to frequency spectra of damage events. The experiment using the datasets of damage related sounds showed that the kernel SOM using KL...
Performance is an important non functional aspect to be considered for any software system. Software Performance Engineering (SPE) is an approach to predict the performance of a software system early in the life cycle. In this paper we present a neural network model for the performance prediction of Multi-Agent system at the early stages of development. We used Feed forward back propagation neural...
Higher-Order Spectral techniques perform well in non-Gaussian signal processing. In this paper, we propose a novel method for lung sounds feature extraction based on AR model bispectrum estimation. By the bispectral cross correlation analysis, select AR model orders and apply them to estimate the parametric bispectrum of the lung sound signals. Then extract bispectrum features of lung sound signals...
In this paper we propose a robust channel estimator for Long Term Evolution (LTE) downlink highly selective using neural network. This method uses the information provided by the reference signals to estimate the total frequency response of the channel in two phases. In the first phase, the proposed method learns to adapt to the channel variations, and in the second phase it predicts the channel parameters...
To estimate the ultimate bound and positively invariant set of a dynamic system is an important but quite challenging task. In this paper, we attempt to investigate the ultimate bounds and positively invariant sets for a class of more general Lorenz-type new chaotic systems. We derive some ellipsoidal estimates of the globally exponentially attractive set and positively invariant set of the general...
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We give an algorithm for this problem that has running time and data requirements polynomial in the dimension and the inverse of the desired accuracy, with provably minimal assumptions on the Gaussians. As a simple consequence of our learning algorithm, we we give the first...
This paper presents Perturbed Frequent Itemset based Classification Technique (PERFICT), a novel associative classification approach based on perturbed frequent itemsets. Most of the existing associative classifiers work well on transactional data where each record contains a set of boolean items. They are not very effective in general for relational data that typically contains real valued attributes...
Quality of service (QoS) provisioning generally assumes more than one QoS measure which implies that QoS routing can be categorized as an instance of routing subject to multiple constraints: delay-jitter, bandwidth, cost, etc. We study the problem of constructing multicast trees to meet the QoS requirements of real-time interactive applications where it is necessary to provide bounded delays and bounded...
This paper presents a hybrid intelligent method to design Morphological-Rank-Linear (MRL) perceptrons to solve the Software Development Cost Estimation (SDCE) problem. The proposed method uses a modified genetic algorithm (MGA) to determine the best particular features to improve the MRL perceptron performance, as well as its initial parameters. Furthermore, for each individual of MGA, a gradient...
A small scale laboratory demonstrator has been constructed to represent a zonal DC distribution system as proposed for future naval vessels. This paper describes how the demonstrator has been used to validate a proposed fault location strategy - Active Impedance Estimation (AIE) - under experimental conditions. The practical processing algorithms required to reduce the effect of noise and the background...
Distributed video coding is a new paradigm for video compression based on the Slepian-Wolf and Wyner-Ziv theorems. Wyner-Ziv video coding, a lossy compression with receiver side information, enables low-complexity video encoding at the expense of a complex decoder. Most of the existing distributed video coding techniques require a feedback channel to determine the number of parity bits for decoding...
Side information generation is a critical step in distributed video coding systems. This is performed by using motion compensated temporal interpolation between two or more key frames (KFs). However, when the temporal distance between key frames increases (i.e. when the GOP size becomes large), the linear interpolation becomes less effective. In a previous work we showed that this problem can be mitigated...
In this paper we present a novel method for high quality real-time video enhancement; it improves the sharpness and the contrast of video streams, and simultaneously suppresses noise. The method is comprised of three main modules: (1) noise analysis, (2) spatial processing, based on a new multi-scale pseudo-bilateral filter, and (3) temporal processing that includes robust motion detection and recursive...
This paper proposes a two-step prototype-face-based scheme of hallucinating the high-resolution detail of a low-resolution input face image. The proposed scheme is mainly composed of two steps: the global estimation step and the local facial-parts refinement step. In the global estimation step, the initial high-resolution face image is hallucinated via a linear combination of the global prototype...
An application of Parallel Radial Basis Function (PRBF) network model on prediction of chaotic time series is presented in this paper. The PRBF net consists of a number of radial basis function (RBF) subnets connected in parallel. The number of input nodes for each RBF subnet is determined by different embedding dimension based on chaotic phase-space reconstruction. The output of PRBF is a weighted...
The question of polynomial learn ability of probability distributions, particularly Gaussian mixture distributions, has recently received significant attention in theoretical computer science and machine learning. However, despite major progress, the general question of polynomial learn ability of Gaussian mixture distributions still remained open. The current work resolves the question of polynomial...
Wave atom transform is a new multi-resolution technique, which has the ability to adapt to arbitrary local directions of a pattern, and to sparsely represent anisotropic patterns aligned with the axes. In this paper, a de-noising technique is proposed to remove the rician noise from Magnetic Resonance Images using wave atom shrinkage. It is well known that the noise in magnetic resonance imaging has...
In this paper, a special design of Uniform Concentric Circular Array (UCCA) is proposed to improve directions of arrival (DoAs) estimation accuracy in fully correlated sources situation. The Centro-symmetry propriety of the introduced antennas shape, as well as each of its subarrays, allow us to develop a Modified Forward/Backward Spatial Smoothing technique (MFBSS) to remove signals' coherence. The...
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