BLDCM新型滑模观测器的无位置传感器控制

针对传统滑模观测器(SMO)抖振和相位延迟问题,提出了一种新型滑模观测器来获取无刷直流电机(BLDCM)反电动势(back-EMF),无需额外增加低通滤波器即能得到光滑的反电动势估计值.由反电动势估计值能够直接计算出转子位置角和转速.根据转子位置角和滞环控制器的输出来选择适当的电压空间矢量,实现无位置传感器控制,并根据转速和反电动势估计值计算转矩.最后,将该滑模观测器用于无磁链环直接转矩控制(DTC)中.实验结果验证了方案的可行性.     

利用反向投影的flash场景自适应视频编码算法

针对闪光造成的光照变化会导致视频帧之间巨大的强度差异问题,提出利用反向投影的flash场景自适应视频编码算法;根据直方图差异提取闪光和非闪光帧,相应地为每个帧分配适当的编码类型,并在加权预测(WP)参数集确定中采用运动向量导数,通过反向投影保证flash场景的全局一致性;实验结果显示,提出的算法在Lena、Peppers、Building、Baboon、Nestling 5个视频上的峰值信噪比(PSNR)值分别可高达32.31 dB、34.14 dB、34.76 dB、34.94 dB、35.05 dB,非常接近原始图像的PSNR;相比其他几种加权预测算法,提出的算法在PSNR及计算复杂度方面均获得了更加优越的编码性能。     

The interaction between skill, postures, forces and back pain in wool handling

Wool handling is an important rural occupation where workers process 200 or more fleeces daily, separating them into various quality components. Loads and postures they experience carry substantial risk of low back pain (LBP). Although a formal skill training structure exists, interaction with loads and LBP is unknown. We examined whether skill and LBP influenced trunk postures and loads of 60 wool handlers representing 3 skill levels. LBP prevalence ranged from 20% for junior (lowest skill) to 45% for open class (highest skill) wool handlers. Open class wool handlers demonstrated increased lateral bend and more axially twisted postures, generating greater medio-lateral shear forces and lateral bend and axial twist moments. LBP was associated with open class wool handlers spending more time in severe axially twisted postures. These findings suggest that skill-based training needs to be reviewed to reduce the quantity of axially twisted posture which may help reduce the prevalence of LBP in this workforce.     

The effect of a lower extremity kinematic constraint on lifting biomechanics

Leaning against a stationary barrier during manual materials handling tasks is observed in many industrial environments, but the effects of this kinematic constraint on low back mechanics are unknown. Thirteen participants performed two-handed lifting tasks using both a leaning posture and no leaning posture while trunk kinematics, muscle activity and ground reaction force were monitored. Results revealed that lifting with the leaning posture required significantly less activity in erector spinae (26% vs. 36% MVC) and latissimus dorsi (8% vs. 14% MVC), and less passive tissue moment compared with the no leaning posture. Peak sagittal accelerations were lower when leaning, but the leaning posture also had significantly higher slip potential as measured by required coefficient of friction (0.05 vs. 0.36). The results suggested that the leaning lifting strategy provides reduced low back stress, but does so at the cost of increased slip potential.     

溶剂系统的模式识别

通过三层ＢＰ人工神经网络,对溶剂系统进行模式识别。以经规格化自理伯Ｘｔ、Ｘｅ、Ｘｍ、Ｘｎ、Ｘｄ这５个溶剂性质的选择性参数作为判别指标,５类共１９种不同的溶剂作为训练样本,得到最佳网络参数。然后以十我种有代表性的溶剂作为待测样本进行了模式识别。研究结果表明,人工神经网络用于溶剂系统的模式识别,识别结果与实际一致,本文结果有助于色谱分析及分离技术中溶剂的选择。     

GIS环境下的最佳路径规划

本文从沈阳市消防通信指挥系统的实际需要出 发,在GIS环境下求解从消防中队到火灾发生地的最佳路径．采用了离线搜索、建立最佳路 径库来解决实际应用中对实时性的要求,叙述了如何建立最佳路径的数学模型和利用遗传算 法通过样本路径来求解模型中的参数．     

隐马尔可夫模型的一种有区分力的反向传播训练方法

研究隐马尔可夫模型(HMM)的一种有区分力的训练方法.在多层前向神经网络的 框架中实现了HMM的前向概率计算.基于这一框架,利用偏导数的反向传播计算方法,通 过梯度上升的优化过程来实现互信息的最大化,从而对HMM进行有区分力的训练.这一 训练方法被称之为HMM的反向传播训练方法.此外,还设计了一个用以实现这一训练方 法的在数值计算上具有强鲁棒性的算法.语音识别的实验结果证实了这一训练方法的优越 性.     

Feedforward networks in financial predictions: the future that modifies the present

The main goal of this paper is to show how relatively minor modifications of well-known algorithms (in particular, back propagation) can dramatically increase the performance of an artificial neural network (ANN) for time series prediction. We denote our proposed sets of modifications as the 'self-momentum', 'Freud' and 'Jung' rules. In our opinion, they provide an example of an alternative approach to the design of learning strategies for ANNs, one that focuses on basic mathematical conceptualization rather than on formalism and demonstration. The complexity of actual prediction problems makes it necessary to experiment with modelling possibilities whose inherent mathematical properties are often not well understood yet. The problem of time series prediction in stock markets is a case in point. It is well known that asset price dynamics in financial markets are difficult to trace, let alone to predict with an operationally interesting degree of accuracy. We therefore take financial prediction as a meaningful test bed for the validation of our techniques. We discuss in some detail both the theoretical underpinnings of the technique and our case study about financial prediction, finding encouraging evidence that supports the theoretical and operational viability of our new ANN specifications. Ours is clearly only a preliminary step. Further developments of ANN architectures with more and more sophisticated 'learning to learn' characteristics are now under study and test.     

关于BP算法推导过程与讨论

本文通过对多层神经网络模型的BP算法的推导,讨论用BP算法对网络进行优化后误差精度、网络结构和学习次数之间的关系,最后指出BP算法的不足之处,提出加快学习过程的一些方法和技巧。     

一种脱线式数字现金系统

本文给出了一个基于RSA加密系统的脱线式数字现金支付系统。该系统利用隐藏、签证和加密等技术保证了合法数字现金的不可追踪性,保护了用户的隐私权。同时系统具有很强的侦测用户欺骗的能力,用户一旦进行欺骗,系统可以立刻追查其身份,以保障数字现金的安全性。