低信噪比通信信号的自适应调参随机共振方法

参数调节随机共振系统中参数的选择对输出信号的效果优劣具有决定性作用.本文针对目前随机共振无法通用地处理多类微弱通信信号的问题，提出基于自适应调参随机共振的信号增强方法.首先，从信号的特征子空间角度阐释了随机共振的能量转移本质，提出将基于奇异值分解的测度函数作为评价函数进行寻优.其次，在分析了两个不同系统参数的作用后，利用幅度归一化对单参数优化，降低了复杂度，并将滑动平均滤波器加入随机共振模块来防止幅度漂移.最后，以人工鱼群算法为基础，模块化设计出方法的整体框架和具体步骤.仿真结果表明，针对四类共九种信号，该方法能够以平均4至5次的迭代收敛速度实现带噪声的信号和非线性系统的匹配.     

基于自适应阈值活动语音检测和最小均方误差对数谱幅度估计的低信噪比降噪算法

针对低信噪比(SNR)环境下传统方法对声信号降噪的局限性，提出了一种联合自适应阈值活动语音检测（VAD）算法和最小均方误差对数谱幅度估计（MMSE-LSA）的实时降噪算法。首先，在VAD算法中通过基于能量概率最大值的概率统计来对背景噪声进行估计，对得到的背景噪声进行实时更新并保存；然后，将实时更新的背景噪声作为MMSE-LSA的参考噪声，并对噪声幅度谱进行自适应更新，最后进行降噪处理。通过在真实场景中对四类声信号进行实验，结果表明，该算法在保证对低SNR声信号的实时处理的情况下，相较于传统MMSE-LSA算法，降噪信号的SNR能够提高10~15 dB，且不存在信号过减的情况，可应用于实际工程。     

Design of a low cross‐talk micro‐coil array for micro‐scale MRI

Design of magnetic resonance micro‐coil arrays with low cross‐talk among the coils can be the main challenge to improve the effectiveness of magnetic resonance micro‐imaging because the electrical cross‐talk which is mainly due to the inductive coupling perturbs the sensitivity profile of the array and causes image artifacts. In this work, a capacitive decoupling network with N(M ? 1) + (N ? 1)(M ? 2) capacitors is proposed to reduce the inductive coupling in an N × M array. A 3 × 3 array of optimized micro‐coils is designed using the finite element simulations and all the needed elements for the array equivalent circuit are extracted in order to evaluate the effectiveness of the proposed decoupling method by assessing the reduction of the coupled signals after employing the capacitive network on the circuit. The achieved results for the designed array show that the high cross‐talk level is reduced by the factor of 2.2–3.4 after employing the capacitive network. By employing this method of decoupling, the adjacent coils in each row and inner columns can be decoupled properly while the minimum decoupling belongs to the outer columns because of the lack of all necessary decoupling capacitances for these columns. The main advantages of the proposed decoupling method are its efficiency and design easiness which facilitates the design of dense arrays with the properly decoupled coils, especially the inner coils which are more coupled due to their neighbors. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 353–359, 2013     

基于MATLAB软件的组网LPI雷达系统仿真

LPI雷达以其隐蔽性好而被广泛地应用在军事领域,随着网络中心战的飞速发展,多部LPI雷达可以联网组成一个庞大的雷达系统,其在网络对抗体系中为所有作战阶段提供秘密的监视能力和高度态势感知能力上发挥了及其重要的作用。为了更好的评估组网LPI系统的性能,本文首先对组网LPI雷达系统的总SNR进行推导计算,在此基础上用MATLAB软件对多部LPI雷达系统进行仿真,验证了组网雷达相比无组网配置雷达的优越性。     

Adaptive filtering of EEG/ERP through Bounded Range Artificial Bee Colony (BR-ABC) algorithm

In this paper, the Artificial Bee Colony (ABC) algorithm is applied to construct Adaptive Noise Canceller (ANC) for electroencephalogram (EEG)/Event Related Potential (ERP) filtering with modified range selection, described as Bounded Range ABC (BR-ABC). ERP generated due to hand movement is filtered through Adaptive Noise Canceller (ANC) from the EEG signals. ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. Performance of the algorithms is evaluated in terms of Signal-to-Noise Ratio (SNR) in dB, correlation between resultant and template ERP, and mean value difference. Testing of their noise attenuation capability is done on contaminated ERP with white noise at different SNR levels. A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is also made which reveals that ABC algorithm gives better performance in highly noisy environment.     

New Efficient Albedo Monte Carlo Method for Neutron Streaming Analyses

An efficient albedo Monte Carlo method newly developed has been studied by analyzing two types of experiments on neutron streaming. The method is characterized by employing the energy-angle dependent doubly differential albedos for slab, which can be calculated in a short computer time with a one-dimensional transport theory, such as the Sn method and more efficient invariant imbedding method. This paper describes the features of the present albedo Monte Carlo method, including fundamental formulas. In the analyses of the neutron streaming experiments, the calculated results agreed with the measured data within a factor of 2 for a benchmark experiment at the YAYOI reactor and within a factor of 3 for an SNR sodium duct mock-up experiment.

It is concluded that the present albedo Monte Carlo method is practical and applicable to the reactor shielding analysis concerning radiation streaming.     

Noise variance estimation based on dual-channel phase difference for speech enhancement

In this paper, we propose a method for estimating a signal-to-noise ratio (SNR) in order to improve the performance of a dual-microphone speech enhancement algorithm. The proposed method is able to reliably estimate both a priori and a posteriori SNRs by exploring a direction-of-arrival (DOA)-based local SNR that is defined by using spatial cues obtained from dual-microphone signals. The estimated a priori and a posteriori SNRs are then incorporated into a Wiener filter. Consequently, it is shown from an objective perceptual evaluation of speech quality (PESQ) comparison and a subjective listening test that a speech enhancement algorithm employing the proposed SNR estimate outperforms those using conventional single- or dual-microphone speech enhancement algorithms such as the Wiener filter, beamformer, or phase error-based filter under different noise conditions ranging from 0 to 20 dB.     

Radar detection of high-energy cosmic rays in non-Gaussian background using a time-frequency technique

Cosmic rays are the highest-energy observable particles in the universe. Their study opens a new frontier for scientists to better understand the nature of the universe. This paper reports our study of a bistatic radar approach that is being developed for remote sensing of cosmic-ray induced air showers. In this context, we propose a robust detection technique based on time-frequency domain for the received radar echoes. These echoes are modeled as linear-downward chirp signals, characterized by very short sweep periods, low energies, and corrupted by non-stationary and non-Gaussian background noise. In addition, the related parameters of the received echoes are variable within some expected ranges, determined by the physical parameters of the air showers. In this paper, we explore the performance of the proposed detection method through an extensive theoretical analysis. We derive formulae for probability of the correct detection, as well as false-alarm rate. Numerical simulations and experimental results that corroborate our analysis are also presented.     

A low complexity digital unit for scalar linear interpolation and compression

A linear interpolator with compressed output and its alternative version that supports error correction are presented in this paper. The interpolation devices can be driven by an Analog/Digital Converter (ADC) that accepts as input, low frequency signals, like sensor values. The proposed interpolation methods can correct ADC linearity errors and increase the dynamic resolution of an ADC or they can reconstruct a signal from fewer samples in non-uniform distance. If the input signal is partially exponential or logarithmic then, specific correction rules can be employed to achieve a lower signal quantization error. These rules are based on simple operations like shifts and comparisons and thus, they can be implemented using low complexity hardware. Spline, Linear, Quadratic interpolation, popular compression tools and reference signals are used to evaluate the experimental results. The proposed architecture is scalar since multiple interpolators can be connected in series. A 3-stage interpolator with 9-bit input and 12-bit typical output resolution was tested with sinusoidal input. The Signal to Noise and Distortion Ratio (SNDR) of the ADC that has been used was increased up to the double. The proposed method was also tested using a pressure sensor, an acoustic signal and image reconstruction leading to Mean Square Error (MSE) that is up to 10 times lower. The achieved compression ratio, ranges between 11% and 76%. The implementation complexity of a one stage interpolator with 9-bit input resolution requires 583 Logic Elements (LE) i.e., less than 3% of the LEs that exist in an Altera Cyclone III EP3C25N Field Programmable Gate Array (FPGA).     

Hybrid Taguchi-Immune Algorithm for the thermal unit commitment

In this paper, a Hybrid Taguchi-Immune Algorithm (HTIA) is presented to deal with the unit commitment problem. HTIA integrates the Taguchi method and the Traditional Immune Algorithm (TIA), providing a powerful global exploration capability. The Taguchi method (TM) is incorporated in the crossover operations in order to select the better gene for achieving crossover consequently, enhancing the TIA. It has been widely used in experimental designs for problems with multiple parameters. The effectiveness and efficiency of HTIA are demonstrated by presenting several cases, and the results are compared with previous publications. Our results show that the proposed method is feasible, robust, and more effective than many other previously developed computation algorithms.