Power Dissipation in Spintronic Devices Out of Thermodynamic Equilibrium

Quantum limits of power dissipation in spintronic computing are estimated. A computing element composed of a single electron in a quantum dot is considered. Dynamics of its spin due to external magnetic field and interaction with adjacent dots are described via the Bloch equations. Spin relaxation due to magnetic noise from various sources is described as coupling to a reservoir. Resulting dissipation of energy is calculated and is shown to be much less than the thermal limit, ∼kT per bit, if the rate of spin relaxation is much slower than the switching rate. Clues on how to engineer an energy efficient spintronic device are provided.     

利用独立分量分析法去除地震噪声

 独立分量分析（ICA）作为盲源分离（BSS）的一种新方法,是分解观测数据中独立信息的有力工具。以往的ICA算法一般假设噪声可以忽略不计，而实际的观测数据中又常常包含一些加性噪声。对于加性噪声的影响不能忽略的情况下，改进的ICA算法首先利用非零时间滞后协方差，应用两步特征值分解法(EVD)可成功地去除部分加性噪声的影响；再利用ICA算法就能更好地分离出原信号。本文通过对地震理论模型和实际资料的试验，说明改进的ICA算法能够有效地克服加性噪声对常规ICA算法的影响，能够分离出地震资料中的有效信号，从而实现利用独立分量分析压制地震资料噪声的目的。     

A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.     

可追溯的绿色安全猪肉生产系统研究

现在，养猪生产者滥用激素、微量元素和违禁药物饲养生猪，而消费者却无法识别这种猪肉，严重地威胁着消费者的食品卫生安全。为此，应用射频识别技术，采用综合软件管理，以一维条形码实行三网合一查验的方式来建立猪肉生产卫生安全跟踪系统，是保障消费者食品卫生安全的理想方法。     

降低射频电路串扰噪声的布线方法

研究并解决了无障碍多层无网格射频电路的布线问题,主要包括三个部分:设计规则、串扰噪声限制和布线方法.首先通过设计规则计算连线参数,运用RLc模型估算串扰噪声,然后,按照需要连接的实节点个数进行归类并提出相应的布线算法.实验结果表明,该布线方法可有效地降低射频电路的串扰噪声.     

配网侧接入电源对负荷建模的影响

研究了配网侧接入电源对负荷建模的影响。发现当配网侧电源的发电容量逐渐增大时，原有的感应电动机并联恒阻抗、恒电流、恒功率（ZIP）模型的负荷模型将不再能很好地反映该区域的负荷特性，进而提出了一种新的负荷模型结构———异步发电机并联ZIP模型。通过仿真计算，验证了该新负荷模型的有效性，并进一步统一了上述2种负荷模型，称为异步机并联ZIP负荷模型。     

基于隐性故障模型和风险理论的关键线路辨识

在大规模电网中，由简单故障触发的电力系统连锁故障常常会引起大停电的灾难性后果。为了研究复杂电网连锁故障的传播机理，同时找出对连锁故障产生重要影响的关键线路，文中基于模拟连锁故障的隐性故障模型和风险理论，提出了复杂电力系统的线路故障风险评估方法，并辨识出了对系统大停电产生重要影响的一系列关键线路。模型考虑了线路过负荷保护、隐性故障、控制策略及系统运行等参数，对IEEE 118节点系统仿真结果表明，在重负荷状态运行下只对辨识出的少量关键线路加以改善，就可以使系统停电概率大幅减小，特别是大停电概率;在临界状态运行下改善少量关键线路，则可以使系统脱离临界状态，避免大停电发生。     

桥梁颤振气动导数识别的迭代法

本文提出一种利用自由振动响应通过年顿－拉夫逊迭代同时识别出桥梁全部8个颤振气动导的方法。此法具有对迭代初值要求不高，识别结果稳定的特点，并具有一定的抗噪声干扰能力。数字仿真与实物试验结果表明本文方法有效，可行。     

Approximate channel identification via δ‐signed correlation

A method of approximate channel identification is proposed that is based on a simplification of the correlation estimator. Despite the numerical simplification (no multiplications or additions are required, only comparisons and an accumulator), the performance of the proposed estimator is not significantly worse than that of the standard correlation estimator. A free (user selectable) parameter moves ‘smoothly’ from a situation with small sum‐squared channel estimation error but hard‐to‐identify channel peaks, to one with a larger sum‐squared estimation error but easy‐to‐identify channel peaks. The proposed estimator is shown to be biased and its behaviour is analysed in a number of situations. Applications of the proposed estimator to sparsity detection, symbol timing recovery and to the initialization of blind equalizers are suggested. Copyright © 2002 John Wiley & Sons, Ltd.