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Orthogonal frequency division multiplexing access (OFDMA) inherently suffers from large spectral sidelobes, which will lead to interference between users and can not be ignored. In this paper, in order to suppress spectral sidelobes, we propose a novel windowing scheme. The derivation of the optimum window function is based on the solution of an optimization problem. It aims to minimize in-band-out-of-subband...
This paper proposes a regrouping particle swarm optimization-based neural network (RegPSONN) for rolling bearing fault diagnosis. The proposed method applied neural network for rolling bearing conditions classification, and regrouping particle swarm optimization (RegPSO) is utilized for network training, and ten time-domain feature parameters are selected to establish the input vector. To evaluate...
Hyperspectral image (HSI) super-resolution, a technique to obtain higher (often spatial) resolution image from the original image, has been extensively studied and applied to lots of fields such as computer vision, remote sensing, etc. Though fusion based method has achieved state-of-the-art result, it always assume the spatial transformation matrix is given in advance, whereas such a matrix is actually...
We present an automatic method to extract parametric model for RFIC inductors in large modeling space covering a wide range of geometrical variables. We use a modified double-pi network as the equivalent circuit topology of the inductor model. Lumped element values are computed using empirical functions which are formulated in terms of inductor geometries and numerical coefficients. The automated...
With large amount of renewable energy resources integrated into strong coupling interconnected power system (IPS), the conventional automatic generation control (AGC) scheme leads to the increase of the AGC regulation cost and the shortage of the AGC regulation amount in some control areas. In this paper, cooperation of AGC in different control areas was used to solve these problems. Optimal cooperation...
In this paper, we propose a novel resource allocation (RA) scheme based on interference minimization (IM) for cognitive radio networks (CRN). In the approach, we focus on an efficient scheme of subchannels assignment, power allocation and access control for the orthogonal frequency division multiple access (OFDMA)-based secondary users (SUs), accessing licensed spectrums of primary users (PUs) with...
Malware data are typically depicted with extremely high-dimensional features, which lays an excessive computational burden on detection methods. For the sake of effectiveness and efficiency, feature selection is an indispensable part for malware detection. In this paper, we propose an ensemble feature selection method with integration of discriminative and representative properties for malware detection...
We propose a method for extraction of equivalent circuit model for on-chip spiral inductor. The method is based on optimization of circuit elements based on feature points extracted from frequency dependent response. The accuracy of the method is validated by extracting a set of models from electromagnetic simulations of on-chip rectangular spiral inductors. An excellent agreement is achieved between...
In order to solve the problems of traditional Fuzzing technique for software vulnerability detection, a novel method based on code coverage and test cost is proposed. Firstly, static analysis is applied to calculate the code coverage information, including basic block coverage and new block coverage. In addition, test path diversity information is introduced to elevate path coverage, which is achieved...
Virtual machine (VM) management in cloud data center is an important problem that remains to be effectively addressed. There has been a considerable amount of work investigating the management of physical-to-virtual resource mappings to improve the efficiencies of resource usage and power consumption in data center. However, these different management objectives are conflicting. One solution can't...
This paper aims to investigate the resource allocation problem in a relay-assisted OFDMA cognitive radio (CR) system. Different from conventional CR resource allocation problems, a joint bandwidth and power optimization framework using the bandwidth-power product metric is proposed. Besides, rate requirement of the secondary system is satisfied and interference power at the primary receiver is limited...
This paper presents an optimization-based technique to develop silicon substrate for accurate and efficient electromagnetic (EM) simulations. The proposed method simplifies the highly nonlinear substrate doping profile into a few regions with effective conductivities. The accuracy of the optimized substrate is validated against measurement data for two spiral inductors. This simplified substrate enables...
Accurate reconstruction of hyperspectral image(HSI) from a few random sampled measurements is crucial for hyperspectal compressive sensing. The underlying sparsity of HSI is one crucial factor for HSI reconstruction. However, the s-parsity is unknown in reality and varied with different noise. To address this problem, a novel nonseparable sparsity based hyperspectral compressive sensing(NSHCS) method...
Energy efficiency (EE) is an important factor for the deployment of wireless sensor networks. Cooperative communication can help to reduce energy consumption for long distance data transmission. This paper mainly presents the joint optimization of node selection and power allocation for cooperative communication in wireless sensor networks. The proposed brute force approach based on optimal power...
In order to preserve the local structure of the input data, many dimensionality reduction algorithms are involved in the definition of certain locality in the feature space. Thus local patch selection will directly affect the performance of these algorithms. In this paper, we propose a new method of local patch selection for dimensionality reduction. Specially, we incorporate our method into locality-preserving...
Localization is one of the important topics for autonomous driving of unmanned ground vehicle(UGV). Most problems in localization are due to uncertainties in the modeling and sensors. Therefore, various filters method are developed to estimate the states with noise. Recently, particle filter is widely used because it can be applied to the system with nonlinear model and non-Gaussian noise. In this...
While there has been active development of the Linux kernel, little has been done to address kernel bugs with gradually increasing lifetimes. From our statistical analysis, the average lifetime of kernel bugs in each kernel development cycle has increased 2.87 times from the years between 2008 and 2012. This indicates the instability of Linux kernels. To reduce bug lifetime, we present a Kernel Instant...
Multiple kernel learning (MKL) usually searches for linear (nonlinear) combinations of predefined kernels by optimizing some performance measures. However, previous MKL algorithms cannot deal with Lq norm MKL if q
In order to write AVS-P3 audio decoding algorithms in the digital signal processor(DSP) chip which supports fixed-point algorithms, AVS-P3 audio decoding floating-point algorithms need to be converted to fixed-point algorithms. Owing to the high complexity of IMDCT(Inverse Modified Discrete Cosine Transform) module windowing in AVS-P3 decoder algorithm, we propose an improved windowing algorithm in...
To optimize structure and enhance energy-generation capability of monocrystal piezoelectric generator under specific working environment, a analysis model of energy conversion is established. The piezoelectric generator is optimized for different forms of vibration in two-dimensional. For shock style, Design optimization should improve the stress distribution of piezoelectric transducer under the...
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