一种新型指纹锁电路设计

市场上主流的电子锁是基于密码设计的。密码锁的最大的缺陷是密码容易被他人窃取、猜测及遗忘。随着生物技术的发展,越来越多的活体技术应用到识别系统中,如指纹、掌纹、人脸、虹膜等。相对于其它的活体识别技术,指纹识别系统以其可实现性强,成本相对低廉,同时又具备较高的安全性,被越来越多的应用到各种场合。文章给出了一种新型的指纹锁架构,并详细论述了系统的各个组成部分以及指纹识别算法的实现流程。文章对降低系统功耗和增加保密性都提出了独特的方法。     

互联网金融平台中高违约风险用户识别算法

在我国金融科技不断创新的背景下,互联网金融平台中通过网络分析技术开展用户风险识别已经成为当前的热点技术发展方向。以某互联网金融平台的用户交易数据为对象,通过分析其中借贷逾期违约的传播行为,提出通过传播特征构建模型算法识别互联网金融平台的高风险用户。在构建基于阈值传播和随机传播的SIS模型和SIR模型基础上,将模型转换为可评价用户风险值的算法,并进一步与实际违约数据进行验证对比。对比结果显示在前5%和10%高风险群体划分条件下,算法具有较高的召回率和良好的结构关联性。     

基于神经网络的轮胎胎号字符识别

介绍了采用BP神经网络来进行轮胎胎号字符识别的一种尝试性方法。用Matlab来模拟用神经网络进行胎号数字识别这一过程，用投影—变换系数法进行特征提取，确定特征输入、隐含层的神经元和输出后，经训练后可识别胎号，识别率尚可。     

香荚兰豆专题系列之六-影响香荚兰豆萃取物品质的因素及掺假的鉴别

本文主要叙述了作者在十多年来香荚兰豆萃取物的生产研究和学习心得,在我国卷烟、食品、香料香精工业中对香荚兰豆萃取物的加工及应用日益增多的今天,具有一定的参考和借鉴作用。     

Controlling aliased dynamics in motion systems? An identification for sampled-data control approach

Sampled-data control systems occasionally exhibit aliased resonance phenomena within the control bandwidth. The aim of this paper is to investigate the aspect of these aliased dynamics with application to a high performance industrial nano-positioning machine. This necessitates a full sampled-data control design approach, since these aliased dynamics endanger both the at-sample performance and the intersample behaviour. The proposed framework comprises both system identification and sampled-data control. In particular, the sampled-data control objective necessitates models that encompass the intersample behaviour, i.e., ideally continuous time models. Application of the proposed approach on an industrial wafer stage system provides a thorough insight and new control design guidelines for controlling aliased dynamics.     

An EM-based identification algorithm for a class of hybrid systems with application to power electronics

In this paper we present an identification algorithm for a class of continuous-time hybrid systems. In such systems, both continuous-time and discrete-time dynamics are involved. We apply the expectation-maximisation algorithm to obtain the maximum likelihood estimate of the parameters of a discrete-time model expressed in incremental form. The main advantage of this approach is that the continuous-time parameters can directly be recovered. The technique is particularly well suited to fast-sampling rates. As an application, we focus on a standard identification problem in power electronics. In this field, our proposed algorithm is of importance since accurate modelling of power converters is required in high- performance applications and for fault diagnosis. As an illustrative example, and to verify the performance of our proposed algorithm, we apply our results to a flying capacitor multicell converter.     

Fast fingerprint identification for large databases

Fingerprint matching has emerged as an effective tool for human recognition due to the uniqueness, universality and invariability of fingerprints. Many different approaches have been proposed in the literature to determine faithfully if two fingerprint images belong to the same person. Among them, minutiae-based matchers highlight as the most relevant techniques because of their discriminative capabilities, providing precise results. However, performing a fingerprint identification over a large database can be an inefficient task due to the lack of scalability and high computing times of fingerprint matching algorithms.In this paper, we propose a distributed framework for fingerprint matching to tackle large databases in a reasonable time. It provides a general scheme for any kind of matcher, so that its precision is preserved and its time of response can be reduced.To test the proposed system, we conduct an extensive study that involves both synthetic and captured fingerprint databases, which have different characteristics, analyzing the performance of three well-known minutiae-based matchers within the designed framework. With the available hardware resources, our distributed model is able to address up to 400 000 fingerprints in approximately half a second. Additional details are provided at http://sci2s.ugr.es/ParallelMatching.     

The design of experiments,training and implementation of nonlinear controllers based on neural networks

In the area of nonlinear predictive control, several control schemes using artificial neural networks have been proposed. In this work, the issues relating to the information contents of the data used to train the neural network components of these nonlinear predictive control schemes are considered. This raises questions about the design of experiments. A class of feedback-feedforward nonlinear controller based on the model predictive structure (also known as Internal Model Control, IMC, structure) is investigated. The implementation and performance of these neural network based controllers, together with comparisons to other nonlinear and linear controllers, are illustrated on two nonlinear continuous-stirred-tank-reactor simulations.     

New results on PWARX model identification based on clustering approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.