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In this paper we present three optimization techniques of improving the performance of some irregular low-density parity-check ensemble with determinate structure and finite block length. Firstly, its permutation matrix optimization. We present a new random permutation matrix called as the Q-matrix. We substituted Q-matrix for identity matrix in base matrix array which can be expanded into H-matrix...
Support Vector Machines (SVM) has drawn extensive interests due to its attractive properties, based on which some dimensionality reduction methods have been proposed. However, SVM here only serves as a feature extractor rather than a classifier, the extracted features are in turn used as inputs to other different classifiers. In this paper, a novel and simpler SVM-induced Dimensionality Reduction...
Spectrum sensing has been identified as a key enabling functionality to ensure cognitive radios would not interfere with primary users; however, it always faces the hard challenge in a low signal-to-noise (SNR) radio region. In this paper, we optimize spectrum sensing algorithm which combines backward linear prediction and QR decomposition of the over-sampled received signals. We propose an adaptive...
This article mainly introduces the method of TOPSIS and describes in much detail the application of TOPSIS in seeking the optimum method of blended coal by confirming the weight of index with entropy. A blended coal combustion in power plant issue as an example, optimum method is selected under the condition that four aims and four kinds of blended coals. The method can combine qualitative analysis...
The decision of reservoir flood operation including quantitative indexes and qualitative indexes is a multiple attribute semi-structural decision-making problem. Aiming at the un-reasonability of qualitative indexes described by defining-numbers, interval numbers based on duality contrast and mood operator are proposed to describe the relative membership degree of qualitative indexes instead of defining-numbers...
Aimed at the object recognition problem in which the characteristic values of object types and observations of sensors are in the form of triangular fuzzy numbers, a new fusion method for multi-sensor data is proposed based on mean deviation. The method defines the distance matrix between all object types and unknown object. After solving the optimization problem of maximizing the mean deviations...
Computing the multi-constrained quality of service (QoS) routing according to multi-dimensions vector will cause that actual transmission route is inconsistent with optimal theoretical route and that QoS cannot meet requirements. To solve this, a novel multi-constrained QoS routing algorithm based on vector converting is proposed. The multi-dimensions vector space, which is composed of multiple additive...
Multiple-input multiple-output (MIMO) systems assisted by multiple relays with single antenna are considered. The signal transmission consists of two phases. In the first phase, the source node broadcasts the vector symbols to all relays, then all relays forward the symbols multiplied by gain parameters to the destination simultaneously. Unlike the case of full cooperation among relays such as a single...
In this paper, we consider a relay system in multiple-input multiple-output (MIMO) multi-user channels where a single MIMO relay is engaged in communication between multiple source-destination terminal pairs. We propose two amplify-and-forward (AF) relaying schemes which maximize the sum-rate for the interference channel with multiple source-destinations. First, we introduce an iterative scheme which...
In this paper, the downlink performance of distributed antenna systems (DAS) with random antenna layout is investigated. We consider the composite channel including large-scale fading and small-scale fading. When the large-scale channel state information, which usually varies slowly and is easy to be obtained, is available at the transmitter, the problem of power allocation among distributed antennas...
This paper analyzes the rate of convergence of a distributed averaging scheme making use of memory at each node. In conventional distributed averaging, each node computes an update based on its current state and the current states of their neighbours. Previous work observed the trajectories at each node converge smoothly and demonstrated via simulation that a predictive framework can lead to faster...
This paper introduces the classical Dijkstra algorithm in detail, and illustrates the method of implementation of the algorithm and the disadvantages of the algorithm: the network nodes require square-class memory, so it is difficult to quantify the shortest path of the major nodes. At the same time, it describes the adjacent node algorithm which is an optimization algorithm based on Dijkstra algorithm...
To the question of multi-attribute decision making in threat assessment (TA), for improving the reliability of TA and enhancing the quality of assessment, an intuitionistic fuzzy preference information based TA approach on multi-attribute decision making is proposed. Firstly, built the intuitionistic fuzzy interzone judgement matrix; secondly, gived the normalization method for target attributes with...
In this paper, the characteristic basis function method (CBFM) is applied to instead of conventional MOM for MLFMA implementations. CBFM includes the mutual coupling effects among different subdomains directly by constructing the high level basis functions, use of these basis functions leads to a significant reduction in the number of unknowns, and results in a substantial size reduction of the coupling...
Privacy is the most important apprehension in many data mining applications. In this paper a new technique called Cryptic Random Projection, solves the re-identification quandary (which is found in the conventional random projections).Here this encryption based random projection assigns secret keys to the positions of random matrix elements and not to the random numbers. We have addressed two kinds...
This paper presents a novel method based on Hopfield neural networks (HNN) for cross-layer dynamical resource allocation in orthogonal frequency division multiple access (OFDMA)-based wireless mesh networks (WMN). The objective is to optimize the maximization of the system throughput using HNN under the conditions of the signal-to-interference-plus-noise ratio (SINR) constraint, power constraint and...
Along with the growing energy consumption of modern society, the environmental protection of power system becomes more important. In this paper, the environmental impacts on thermal power plants are considered in optimal power flow, and a new method to determine the weight of objective function is proposed. Thermal power plant's geographical location, weather conditions and the impact of population...
Cable-driven parallel manipulators (CDPMs) are a special class of parallel manipulators that are driven by cables instead of rigid links. So CDPMs have a light-weight structure with large reachable workspace. The aim of this paper is to provide the kinematic analysis and the design optimization of a cable-driven 2-DOF module, comprised of a passive universal joint, for a reconfigurable system. This...
A novel domain decomposition approach for modeling electrically small details within large computational domains is proposed. The approach tackles the conditioning issues associated with highly non-uniform finite element meshes resulting from direct discretization of fine geometrical details. The proposed method addresses this particular challenge, specifically for fast optimization tools, by separating...
Independent component analysis (ICA) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. This paper proposes a new extended model for CT medical image de-noising, which is using independent component analysis and dynamic fuzzy theory. Firstly, a random matrix was produce to separate the CT...
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