半桥三电平双有源桥不对称均压控制策略

半桥三电平双有源桥(HBTL-DAB)电路工作时必须解决三电平侧上下直流母线电容均压问题,在传统对称控制模式中,可通过微调占空比的方法,实现带载情况下的电容电压均衡控制。然而在空载情况下,对称控制模式难以从控制策略上实现上下直流母线电容电压的均衡调节。针对该问题,文中提出一种针对HBTL-DAB电路的不对称控制方法,首先从理论上分析对称模式不能均压的原因,进而根据不对称方法计算空载时上下直流母线电容分别在正负半周期内传输的能量偏差。通过调节该能量偏差实现上下直流母线电容电压的均衡控制,并同时指出影响电压均衡控制效果的主要因素。最后通过仿真,对所述不对称控制方法在多种工况下的运行情况进行验证。结果表明,无论是外部持续存在不平衡因素的工况、只存在初始不平衡因素的工况,还是内部存在脉冲误差的工况,不对称控制方法都能实现空载和带载时的电压均衡控制。     

Battery charge equalization circuit with a multi-winding transformer

This study proposes a battery charge equalization circuit with a multi-winding transformer. A full-bridge converter with soft switching is applied at the primary side of a multi-winding transformer for reducing the switching loss and increasing the system efficiency. A voltage doubler type rectifier is used at the secondary side of multi-winding transformer to decrease the number of transformer windings and the conduction loss. The important advantages of the proposed circuit include the following: The charge current is limited by the transformer leakage inductance without any choke inductor, and charge equalization is realized by adjusting the transformer’s turn ratio. A measurement index, charge equalization performance (C.E.P.), is introduced for the performance measurement of the charge equalization method. In experiments, four LiFePO₄ battery modules are connected in series and discharged at different C-rates. The experimental results show that the discharging time of the series-connected battery modules can be greatly increased using the proposed battery charge equalization circuit.     

共生生物搜索算法在水声信道均衡中的应用

由于多径效应和频散效应导致水声信道中声信号衰减和失真严重,传统均衡技术不能满足在水声信道中应用的要求,近年来神经网络在均衡技术方面的突出表现受到广泛关注,因此,本文提出一种高效的神经网络训练算法,即基于非线性自回归神经网络的改进共生生物搜索算法(简称NARX-nSOS算法)实现水声信道均衡。该算法在非线性自回归神经网络(Nonlinear Autoregressive Neural Network with Exogenous Inputs, NARX)均衡器的基础上,用共生生物搜索算法(Symbiotic Organisms Search, SOS)来进行优化,并结合反向学习算法(Opposition-Based Learning, OBL)来提高该算法的收敛能力,利用计算机对NARX-nSOS算法的有效性进行了仿真验证,结果证明NARXnSOS算法加快了收敛速度,通信质量得到了显著提高。     

Medical image contrast enhancement based on improved sparrow search algorithm

The collection or transmission of medical images is often disturbed by various factors, such as insufficient brightness and noise pollution, which will result in the deterioration of image quality and significantly affect the clinical diagnosis. To improve the quality of medical images, a contrast enhancement method based on improved sparrow search algorithm is proposed in this paper. The method is divided into two steps to enhance the medical images. First, a new transform function is introduced to improve the brightness or contrast of medical images, and two parameters in the transform function are optimized by the improved sparrow search algorithm. Second, adaptive histogram equalization method with contrast limited is used to equalize the result image of the previous step to make the pixel distribution of the image more uniform. Finally, a large number of experiments and qualitative and quantitative analyses were conducted on the common data sets. The analysis results demonstrate that the presented approach outperforms some existing medical image processing approaches.     

A closed-form derivation of self and multi-user interference for time-reversed UWB communications

Multipath degradation is a significant consideration for all wireless communication systems. A time-reversed UWB system harnesses the multipath channel to achieve temporal and spatial focusing through signal pre-filtering at the transmitter side. In cases where the RMS delay spread of a channel is larger than a user’s transmitted pulse separation, inter-pulse, -frame, and -symbol interference may occur. Of even more concern is multi-user interference, which significantly reduces system performance. This paper presents closed-form expressions for self and multi-user interference for a UWB system utilizing a time-reversed approach. The influence of user multiplexing codes is taken to account through incorporation of a ‘separation probability’, which characterizes a family of hopping sequences. The standardized IEEE 802.15.3a channel model is applied, and the derived performances are compared with that of a simulated time hopped time-reversed UWB system.     

保持图像细节的直方图均衡算法

对常规的直方图均衡算法进行了改进,避免了不同灰度的像素均衡后被合并、图像细节丢失等现象.实验结果表明,改进的直方图均衡新算法既能充分增强图像的对比度,又能保持图像的局部细节,使图像具有更加自然的视觉效果.     

脑电信号中眼电伪迹的自动去除算法

为实现眼电伪迹的自动去除,提高算法的有效性和稳健性,提出一种眼电伪迹自动去除算法。采用样本熵和一种通用的伪迹判决方法对眼电伪迹进行自动识别,通过脑电信号的重构实现眼电伪迹的去除。实验结果表明,对于不同长度的真实脑电信号,该算法均能准确地去除眼电伪迹,较好地保留其他的脑电信号成分,且可以完全自动地去除眼电伪迹,适用于实时场合。     

A blind watermarking method using maximum wavelet coefficient quantization

This paper proposes a blind watermarking algorithm based on maximum wavelet coefficient quantization for copyright protection. The wavelet coefficients are grouped into different block size and blocks are randomly selected from different subbands. We add different energies to the maximum wavelet coefficient under the constraint that the maximum wavelet coefficient is always maximum in a block. The watermark is embedded the local maximum coefficient which can effectively resist attacks. Also, using the block-based watermarking, we can extract the watermark without using the original image or watermark. Experimental results show that the proposed method is quite robust under either non-geometry or geometry attacks.     

频域单源区间和欠定的盲信号分离

探讨在感知器个数少于源信号个数时的盲分离问题,提出频域中的单源区间矩阵恢复方法,以实现时域检索平均法在频域中的扩展,与传统的聚类算法相比,该算法计算简单、精度高,在理论上能够无偏差地估计混叠矩阵。在源信号的恢复上,根据稀疏的原则,在仅m个源在频域中较大、其余源可近似为0的假设下,得出求解L1范数的简化方法。语音信号仿真实验展示了该方法的性能和实用性。     

Image contrast enhancement using fuzzy clustering with adaptive cluster parameter and sub-histogram equalization

Histogram equalization is an effective technique to boost image quality and contrast enhancement. However, in some cases the increase in image contrast by traditional histogram equalization exceeds the desired amount Which damages the image properties and wanes its natural look. Histogram division and performing a separate equalization for each sub-histogram is one of the presented solutions. The dividing method and determining the number of sub-histograms are the main problems directly affecting the output image quality. In this study, a method is introduced for automatic determination of the number of sub-histograms and density based histogram division leading to appropriate output with no need for parameter setting. Each main peak is in a separate section. Image contrast is increased with no loss of image specifications through determining the number of sub-histograms based on the number of main peaks. The introduced histogram equalization approach consists of three stages. The first stage, using histogram analysis, produces an automated estimate of number of clusters for image brightness levels. The second, clusters the image brightness levels, and using the provided transfer function, the final stage includes contrast enhancement for each individual cluster separately. The results of the proposed approach demonstrate not only clearer details along with a boost in contrast, but also noticeably more natural appearance in the images.