An advanced system for the automatic classification of multitemporal SAR images

A novel system for the classification of multitemporal synthetic aperture radar (SAR) images is presented. It has been developed by integrating an analysis of the multitemporal SAR signal physics with a pattern recognition approach. The system is made up of a feature-extraction module and a neural-network classifier, as well as a set of standard preprocessing procedures. The feature-extraction module derives a set of features from a series of multitemporal SAR images. These features are based on the concepts of long-term coherence and backscattering temporal variability and have been defined according to an analysis of the multitemporal SAR signal behavior in the presence of different land-cover classes. The neural-network classifier (which is based on a radial basis function neural architecture) properly exploits the multitemporal features for producing accurate land-cover maps. Thanks to the effectiveness of the extracted features, the number of measures that can be provided as input to the classifier is significantly smaller than the number of available multitemporal images. This reduces the complexity of the neural architecture (and consequently increases the generalization capabilities of the classifier) and relaxes the requirements relating to the number of training patterns to be used for classifier learning. Experimental results (obtained on a multitemporal series of European Remote Sensing 1 satellite SAR images) confirm the effectiveness of the proposed system, which exhibits both high classification accuracy and good stability versus parameter settings. These results also point out that properly integrating a pattern recognition procedure (based on machine learning) with an accurate feature extraction phase (based on the SAR sensor physics understanding) represents an effective approach to SAR data analysis.     

An atrioventricular node model for analysis of the ventricular response during atrial fibrillation

This paper introduces a model of the atrioventricular node function during atrial fibrillation (AF), and describes the related ECG-based estimation method. The proposed model is defined by parameters that characterize the arrival rate of atrial impulses, the probability of an impulse choosing either one of the two atrioventricular nodal pathways, the refractory periods of these pathways, and the prolongation of the refractory periods. These parameters are estimated from the RR intervals using maximum likelihood estimation, except for the shorter refractory period which is estimated from the RR interval Poincaré plot, and the mean arrival rate of atrial impulses by the AF frequency. Simulations indicated that 200-300 RR intervals are generally needed for the estimates to be accurate. The model was evaluated on 30-min ECG segments from 36 AF patients. The results showed that 88% of the segments can be accurately modeled when the estimated probability density function (PDF) and an empirical PDF were at least 80% in agreement. The model parameters were estimated during head-up tilt test to assess differences caused by sympathetic stimulation. Both refractory periods decreased as a result of stimulation, and the likelihood of an impulse choosing the pathway with the shorter refractory period increased.     

A system for the automatic recognition of moving patterns

A system for the automatic recognition of two-dimensional patterns is described; recognition taking place as images of the patterns move in a rapid nonstop manner across a stationary scanning unit which takes the form of a bank of photodiodes. Although emphasis is placed on the recognition of alphabetic and numeric characters, the principles developed are applicable to the recognition of more general types of two-dimensional patterns. The theoretical principles on which the system is based are developed in Section II and experimental and computer simulation results are given and discussed in Section III. In Section IV the difficulties involved in the manual design of the recognition "logic" are considered and reference is made to a machine algorithm for the automatic design and testing of a complete recognition system. Some results obtained when using the algorithm are presented.     

Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation

A new method for QRST cancellation is presented for the analysis of atrial fibrillation in the surface electrocardiogram (ECG). The method is based on a spatiotemporal signal model which accounts for dynamic changes in QRS morphology caused, e.g., by variations in the electrical axis of the heart. Using simulated atrial fibrillation signals added to normal ECGs, the results show that the spatiotemporal method performs considerably better than does straightforward average beat subtraction (ABS). In comparison to the ABS method, the average QRST-related error was reduced to 58 percent. The results obtained from ECGs with atrial fibrillation agreed very well with those from simulated fibrillation signals.     

一种心电监测和房颤预警系统的研究

随着社会进步和经济的发展,在人们生活水平提高的同时,各种心血管疾病成为人类健康的隐形杀手。本文提出了一种基于嵌入式架构的便携式心电监测和房颤预警系统,实现了受试者心电信号实时采集监测的功能,采集数据通过无线网络传输至云端进行存储,监测者可以远程获取云上存储的心电监测数据,下载并采用基于主分量解析分析去获取受试者心电房颤的特征信息,准确判断受试者是否出现房颤的情况,从而实现受试者的心脏健康状况,监测结果可以在监测设备显示屏以及远程安卓手机的APP程序中进行显示。本研究所开发的系统具有成本低廉、操作简便、运行可靠等优势。     

Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes

Currently, no reliable method exists to predict the onset of paroxysmal atrial fibrillation (PAF). We propose a predictor that includes an analysis of the R-R time series. The predictor uses three criteria: the number of premature atrial complexes (PAC) not followed by a regular R-R interval, runs of atrial bigeminy and trigeminy, and the length of any short run of paroxysmal atrial tachycardia. An increase in activity detected by any of these three criteria is an indication of an imminent episode of PAF. Using the Physionet database of the Computers in Cardiology 2001 Challenge, the predictor achieved a sensitivity of 89% and a specificity of 91%.     

Time domain and spectral analysis of electrograms in man during regular ventricular activity and ventricular fibrillation

Electrogram signals from intramyocardially placed wire electrodes were recorded in 24 open heart surgery patients during regular heart activity (RHA) and ventricular fibrillation (VF). Time domain parameters, maximal amplitudes (AMAX, UMAX), maximal derivatives (DMAX, SMAX), and power spectra in the frequency region up to 100 Hz were analyzed off-line on a digital computer. DMAX, AMAX, SMAX, and UMAX were significantly lower postoperatively than during the operation in RHA, median values reduced by 37, 23, 54, and 50 percent. Corresponding reductions in median values of 64, 39, 58, and 30 percent occurred in the transition from RHA to VF during the operation (peroperatively).     

Atrial activity extraction for atrial fibrillation analysis using blind source separation

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA and VA present non-Gaussian distributions; and 3) the generation of the surface ECG potentials from the cardioelectric sources can be regarded as a narrow-band linear propagation process. To empirically endorse these claims, an ICA algorithm is applied to recordings from seven patients with persistent AF. We demonstrate that the AA source can be identified using a kurtosis-based reordering of the separated signals followed by spectral analysis of the sub-Gaussian sources. In contrast to traditional methods, the proposed BSS-based approach is able to obtain a unified AA signal by exploiting the atrial information present in every ECG lead, which results in an increased robustness with respect to electrode selection and placement.     

一种基于ARM的多路光纤自动保护系统

介绍了一种基于ARM+Linux的多路光纤自动保护倒换系统,采用ARM+Linux的高速数据采集平台,实时监测多路光纤光功率并智能判别光纤状态,当监测到光纤线路发生故障时,利用光开关及时有效地在工作光纤和保护光纤之间进行自动切换,并把故障信息通过网络告知监测站.     

An expert system for land cover classification

A framework to represent a broad class of problems in the analysis of remote sensing imagery is proposed, and an inference engine to tackle such problems is derived. A simple model for spectral knowledge representation is used along with a method for quantification of knowledge through an evidential approach. An automatic knowledge extraction technique is also proposed to gather knowledge from training samples. The techniques of knowledge extraction, representation and inferencing have been used to do a land cover analysis on two data sets, and the results are compared with contemporary digital techniques. It is found that the proposed approach has the advantages of avoiding commission errors, and can incorporate non-spectral and collateral knowledge, while its accuracy using only spectral knowledge is comparable with standard digital methods     

A new method for analysis of atrial activation during chronicatrial fibrillation in man

To further clarify the mechanisms maintaining chronic atrial fibrillation (CAF), a method identifying preferable activation patterns of the atria during fibrillation, by time averaging of multiple discrete excitation vectors, was developed. Repeated recordings, each of 56 atrial bipolar electrograms simultaneously acquired during 8 s, were made at multiple sites in the right atrial free wall and the left atrial appendage in 16 patients with CAF using a 2.17×3.54 cm electrode array. The local activation times (LAT's) in each recording were estimated as the median activation time at the respective measurement point. By calculating the time difference between the LAT's at adjacent measurement points in two spatial dimensions, a direction vector was created for each activation wave passing each set of measurement points, a total of 42 sets. By time averaging of the individual direction vectors (typically n=55) at each set of measurement points, preferable activation patterns were determined. Three types of activation patterns were found: 1) inconsistent activation (n=5), 2) consistent activation with preferential propagation directions (n=7) and 3) consistent activation with impulses originating from a localizable site within the recording area (n=4). All activation patterns were reproducible and the two latter patterns were proven significant using statistical tests. It is concluded that this new method is useful in further clarification of the mechanisms involved in the maintenance of atrial fibrillation     

Spectral analysis of arterial blood pressure in the rat during atrial fibrillation

This paper describes the development of a systems identification protocol in the rat for use in studies of the dynamics of blood pressure control The method is based on Taylor's canine random heart model and employs electrically induced atrial fibrillation to generate random fluctuations in arterial blood pressure. In order to evaluate the utility of the protocol, recordings of pulsatile blood pressure were obtained from the femoral arteries of anesthetized rats during atrial fibrillation. The data were reduced to spectral density function estimates using standard techniques of discrete spectral analysis. The results indicate that during atrial fibrillation, the time course of arterial blood pressure constitutes a white noise source in the frequency band from 0.01 to 10 Hz, in sharp contrast to the concentration of energy from the normal cardiac cycle into narrow frequency bands within this range. Thus, the protocol should be useful in the analysis of the dynamics of most physiological processes which respond to changes in blood pressure.     

有线电视交互式自动点播系统

介绍在现有普通有线电视基础上，增加交互式自动节目点播系统的构成方法。     

An integrated automatic design system for complex DSP algorithms

An integrated design environment for the automated design of DSP systems is described. The overall design time of complex DSP systems on silicon can be reduced drastically by offering the designer a complete silicon compilation environment, integrating architectural level synthesis tools, a module generator and a floorplanner. The system is supported by a flexible and powerful library. A true exploration of the design space in an interactive way is possible. Examples of the first complex chips that have been designed with this system are discussed.     

Discrimination of atrial fibrillation from regular atrial rhythmsby spatial precision of local activation direction

This study tests the hypothesis that atrial fibrillation (AFib) can be discriminated from regular atrial rhythms by a measure of the variation in local activation direction. Human endocardial atrial recordings of AFib, sinus rhythm, atrial flutter, and supraventricular tachycardia were collected using a catheter with orthogonally placed electrodes, and the direction of each activation was calculated using methods previously described by our laboratory. Each recording was divided into segments containing 100 activations, and the spatial precision for each segment was calculated in three dimensions, as well as in each of the three two-dimensional (2-D) planes. The three-dimensional (3-D) spatial precision for 1161 segments of AFib in 11 recordings ranged from 0.09-0.85 (mean=0.45), whereas the spatial precision for 138 segments of regular rhythms in 28 recordings was ⩾0.91 in all but four instances. The 2-D spatial precision values overlapped for all rhythms. The results indicate that 3-D spatial precision of local activation direction is a useful discriminator of AFib     

关于污水处理厂自动控制系统设计分析

随着我国市场经济的快速发展,环境问题已成为了一个严重的问题,其中污水处理问题就是人们需要亟待解决的问题。目前,我国已经建立了很多污水处理厂,其中自动控制系统是污水处理的关键技术,实现了污水处理厂的自动化控制,并且对工艺参数、数据进行采集、分析和管理,保证了出水的达标,提高了生产效率,降低了生产成本。本文主要介绍了污水处理厂自动控制系统的特点和功能,并介绍了自动控制系统的总体设计原则以及对各部分设计进行分析等,希望能保证污水处理厂的自动控制系统设计更加合理。     

自动化仪表控制系统应用分析

在现代技术的推动下,工业生产过程当中自动化仪表设备发挥着越来越重要的作用,为了保证仪表的可靠、稳定的运行,需要依靠有关的控制系统加强对自动化仪表的控制工作,确保其作用能够得到充分发挥,促进工业生产力的发展进步。文章在研究的过程中主要分析了自动化仪表控制系统基本情况,自动化仪表控制系统的特点,以及自动化仪表控制系统的发展趋势。     

短信自动分类的实现

短信自动分类一直以来都是学者研究的热点问题,伴随着各种类别短信的出现,对于用户来说,希望尽可能获取到自己想要看到的短信,因此本文在此问题上提出了利用一种结合黑白名单及时间因素的短信分类器,通过实验表明该分类器可以获得较好的准确率及召回率.     

The time-sequenced adaptive filter for analysis of cardiacarrhythmias in intraventricular electrograms

Implantable antitachycardia devices rely upon schemes for detecting cardiac arrhythmias which utilize rate and its variations; yet rate parameters often identify nonpathologic tachycardias as potentially dangerous and deliver unwarranted therapy. I have developed a predictive filter based upon the time-sequenced adaptive algorithm to be used as a supplement to rate criteria for detecting and identifying serious arrhythmias. The method does not require a fixed template and is independent of a priori patient information. The algorithm also provides arrhythmia diagnosis immediately at the change in rhythm, Algorithmic parameters were determined based upon a training set of patient data, and performance of the technique was evaluated with a completely new test set of 20 arrhythmia passages. The new algorithm yielded a sensitivity and specificity for ventricular tachycardia of 91% and 82% and for ventricular fibrillation of 71% and 93%. Correlation waveform analysis was used to diagnose the same test set of arrhythmias, It yielded a sensitivity and specificity for ventricular tachycardia of 100% and 67% and for ventricular fibrillation of 50% and 100%