Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Comparisons of pharynx, source, formant, and pressure characteristics in operatic and musical theatre singing

Belting, a vocal technique typically cultivated in musical theatre singing, differs timbrally from operatic singing in many interesting respects. The underlying phonatory differences have not been previously investigated in detail. Yet, belting is frequently associated with disturbances of voice function. Articulatory and phonatory characteristics are investigated in a female subject who is a professional singer (co-author JL) trained in both the operatic and belting styles and in an intermediate vocal technique (“mixed”). This article presents data obtained from this subject by video-fiberoptic observation of the pharynx, inverse filtering of airflow, and measurement of subglottal pressure. The results reveal that belting was characterized by very high subglottal pressures and sound levels, and apparently also by a comparatively high degree of glottal adduction. Comparisons with other investigations of related aspects of belting and operatic singing support the assumption that the data obtained from our subject are representative for these vocal techniques.     

核内核子－核子非弹散射截面（Ⅰ）

在与平均场、核内核子－核子弹性散射截面以及输运方程相统一的理论框架内推导了核内核子－核子非弹散射截面的解析表达式．其数值结果能很好地重现自由非弹截面的实验值，所计算的有效非弹截面与Ｄｉｒａｃ－Ｂｒｕｅｃｋｎｅｒ的计算结果相一致．     

数字图像三点中值去隔行技术研究

对传统三点中值去隔行算法进行改进,采用同步更新迭代的方法,提高了图像的画面质量.实验证明,该算法不仅降低了时间复杂度,保护图像边缘,而且明显改善了噪声滤波效果.     

A signal theory approach to the space and frequency variant filtering performed by the human visual system

A mathematical representation is given of the processing performed by the peripheral nervous cells of the human visual system. This representation consists essentially of a set of shift-variant convolutions, implying non-uniform resolutions in both the space and frequency domains. A remarkable property of such “convolutions” is the form-invariance of their outputs with respect to (size) linear scalings of the inputs. It is shown that this latter property is a necessary support of the hypothesis according to which the visual system translates linear scalings of the (retinal) inputs into shifts of the (cortical) outputs.     

可程控核能谱信号放大器设计

为了提高能谱测量系统中放大成形部分的灵活性,采用单片机控制DAC与一级放大结合的方法,研制一种放大倍数可程控的核能谱信号放大器,使其能同时适用于X荧光仪,伽玛谱仪等核能谱测量仪器,实现0～100倍程控放大。试验测试结果表明,设计电路完全达到设计指标要求。     

基于免疫的动态垃圾邮件过滤研究

本文基于生物免疫系统防御机制,探讨了将人工免疫原理应用于垃圾邮件过滤系统(IDSFS),通过动态生成垃圾邮件疫苗,提高系统的检出率.另外,针对传统邮件过滤系统存在的错误肯定率、错误否定率等不足及用户对邮件个性化处理的要求,引入用户反馈机制,使得系统精确率、正确率进一步提高.实验结果表明,该系统具有较强的自学习、自适应能力.     

信道估计在OFDM中的应用

介绍了信道估计在OFDM中的应用,提出一种易于实现的MMSE算法,并对MMSE和LS的性能进行了比较,同时研究了它们的改进算法。结果表明改进算法有很好的性能,可以逼近理想估计。在系统的实现中有较好的参考价值。     

基于中频模板信号的脉冲压缩性能分析

由雷达发射、接收系统导致的信号幅度、相位失真以及由目标径向速度导致的目标多普勒频率是影响脉冲压缩性能的三个主要因素。本文从理论上分析了这三个因素影响脉冲压缩性能的算法原理,通过仿真验证了它们的实际影响效果,对仿真中的情况进行解释说明,对相应指标要求进行了分析,并对在影响脉冲压缩性能的因素存在下的信号处理方法提出了实际的建议。     

定时截尾指数模型验前多数的确定

研究在定时有替换截尾试验下，指数模型点估计的验前参数的确定方法，讨论了验前参数的有关性质并给出了确定验前参数取值适合域的方法．最后用例子说明Ｂａｙｅｓ估计“优于”经典估计．