采用阴影投射法实现的光学并行模糊逻辑

本文提出了一种新的空间编码方法并利用阴影投射系统实现了光学并行模糊逻辑门。本系统可全光学并行实现模糊逻辑中的七种基本逻辑运算,并给出了实验结果。     

Computer-aided tuning of microwave filters using fuzzy logic

This paper introduces an algorithm based on fuzzy logic for tuning microwave filters. The approach is demonstrated by considering two filters: a four-pole Chebyshev filter and an eight-pole elliptic filter. Each filter is then detuned to perform two examples: one is slightly detuned and the other is highly detuned. In both cases, the approach has proven to be very efficient in identifying the filter elements that cause the detuning. The fuzzy rules are extracted from sampled data. The expert rules could also be added. The algorithm can be applied to any microwave circuit tuning problem.     

Deadzone compensation of an XY-positioning table using fuzzy logic

A deadzone compensator is designed for an XY-positioning table using fuzzy logic. The classification property of fuzzy-logic systems makes them a natural candidate for the rejection of errors induced by the deadzone, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy-logic parameters, so that the deadzone-compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded-parameter estimates. Formal nonlinear-stability proofs are given to show that the tracking error is small. The fuzzy-logic deadzone compensator is implemented on an XY-positioning table to show its efficacy.     

Narrowband auscultatory blood pressure measurement

Auscultatory blood pressure measurement uses the presence and absence of acoustic pulses generated by an artery (i.e., Korotkoff sound), detected with a stethoscope or a sensitive microphone, to noninvasively estimate systolic and diastolic pressures. Unfortunately, in high noise situations, such as ambulatory environments or when the patient moves moderately, the current auscultatory blood pressure method is unreliable, if at all possible. Empirical evidence suggests that the pulse beneath an artery occlusion travels relatively slow compared with the speed of sound. By placing two microphones along the bicep muscle near the brachial artery under the occlusion cuff, a similar blood pressure pulse appears in the two microphones with a relative time delay. The acoustic noise, on the other hand, appears in both microphones simultaneously. The contribution of this paper is to utilize this phenomenon by filtering the microphone waveforms to create spatially narrowband information signals. With a narrowband signal, the microphone signal phasing information is adequate for distinguishing between acoustic noise and the blood pressure pulse. By choosing the microphone spacing correctly, subtraction of the two signals will enhance the information signal and cancel the noise signal. The general spacing problem is also presented.     

Hybrid control system design using a fuzzy logic interface

A hybrid control system is proposed for regulating an unknown nonlinear plant. The interface between the continuous-state plant and the discrete-event supervisor is designed using a fuzzy logic approach. The fuzzy logic interface partitions the continuous-state space into a finite number of regions. In each region, the original unknown nonlinear plant is approximated by a fuzzy logic-based linear model, then state-feedback controllers are designed for each linear model. A high-level supervisor coordinates (mode switching) the set of closed-loop systems in a stable and safe manner. The stability of the system is studied using nonsmooth Lyapunov functions. For illustration and verification purposes, this technique has been applied to the well-known inverted pendulum balancing problem.     

ATM traffic management and congestion control using fuzzy logic

The paper focuses on the use of fuzzy logic in network management, ATM congestion control, and ATM switching. The ATM network management ensures traffic agreement at the source level in order to prevent congestion situations from occurring. The paper reviews work in the area of traffic policing and introduces a scheme for improving the performance of a fuzzy policer. The ATM fuzzy switch introduced, enhances the capabilities of the ATM switch, one of the most critical elements in the ATM network     

Fault-tolerant switched reluctance motor drive using adaptive fuzzy logic controller

An adaptive fuzzy controller has been designed to develop a high-performance fault-tolerant switched reluctance motor (SRM) drive. The fuzzy controller continuously adapts its properties to regulate the machine torque as desired by the drive system even under fault conditions. The adaptation of the fuzzy membership functions results in extended conduction period and increased peak current of the healthy phases to deliver the commanded torque, as much as possible. The adaptive fuzzy controller provides smooth torque output with minimum ripple, even under fault conditions, yielding a high-performance SRM drive with fault-tolerant capability.     

The measurement of oxygen saturation in arterial and venous blood

This article describes about the non-invasive optical measurement techniques to assess oxygen saturation in arterial and venous blood. The pulse oximeters for arterial oxygen saturation measurement use light in two wavelengths, in the red and infrared regions, and calibration is used to account for the difference in optical path-length between them. The accuracy of the commercial pulse oximeters is adequate for monitoring patients during surgical operation, where the clinical information that is needed is the absence of dramatic deterioration in the respiration efficiency. However, the error in pulse oximetry is too high for the clinical assessment of lung function, probably because of the need for calibration in the available technique. The use of two wavelengths in the infrared, instead of one wavelength in the red and one in the infrared region, enables the use of pulse oximetry without calibration. The technique can also be used for determining venous blood saturation, which is important for assessment of the adequacy of tissue blood supply.     

模糊逻辑与学习方法的车牌颜色识别算法

针对光照环境复杂多变及各地车牌颜色特征不同的情况,提出了一种结合模糊逻辑与学习方法的车牌颜色识别算法.在HSV颜色空间中进行车牌颜色特征提取,并根据反色信息将车牌颜色识别由一个四分类问题转换为两个二分类问题.对HSV颜色空间三个分量的模糊映射进行加权融合,建立基于隶属度的分类函数,相关参数通过学习算法获得.在一个基于DSP的嵌入式车牌识别平台上进行了与其他传统分类方法的对比实验,结果表明本文算法存两个测试集上都取得了更好的识别效果.     

An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic

Clustering is an effective approach for organizing a network into a connected hierarchy, load balancing, and prolonging the network lifetime. On the other hand, fuzzy logic is capable of wisely blending different parameters. This paper proposes an energy-aware distributed dynamic clustering protocol (ECPF) which applies three techniques: (1) non-probabilistic cluster head (CH) elections, (2) fuzzy logic, and (3) on demand clustering. The remaining energy of the nodes is the primary parameter for electing tentative CHs via a non-probabilistic fashion. A non-probabilistic CH election is implemented by introducing a delay inversely proportional to the residual energy of each node. Therefore, tentative CHs are selected based on their remaining energy. In addition, fuzzy logic is employed to evaluate the fitness (cost) of a node in order to choose a final CH from the set of neighboring tentative CHs. On the other hand, every regular (non CH) node elects to connect to the CH with the least fuzzy cost in its neighborhood. Besides, in ECPF, CH elections are performed sporadically (in contrast to performing it every round). Simulation results demonstrate that our approach performs better than well known protocols (LEACH, HEED, and CHEF) in terms of extending network lifetime and saving energy.     

Call admission control in wideband CDMA cellular networks by using fuzzy logic

In this paper, a novel call admission control (CAC) scheme using fuzzy logic is proposed for the reverse link transmission in wideband code division multiple access (CDMA) cellular communications. The fuzzy CAC scheme first estimates the effective bandwidths of the call request from a mobile station (MS) and its mobility information, then makes a decision to accept or reject the connection request based on the estimation and system resource availability. Numerical results are given to demonstrate the effectiveness of the proposed fuzzy CAC scheme in terms of new call blocking probability/handoff call dropping probability, outage probability, and resource utilization.     

Vertical handover-decision-making algorithm using fuzzy logic for the integrated Radio-and-OW system

Abstract-Due to the complementary nature of radio and optical wireless (OW) both in capacity and coverage, the combined use of both for data transmission could have advantages over a single media. However, big technical challenges for vertical-handover (VHO) strategy arise for such an integrated system. According to different interruption types and traffic modes, two basic VHO schemes can be applied: immediate VHO (I-VHO) and dwell VHO (D-VHO). This paper proposes a novel fuzzy-logic (FL)-based decision-making algorithm for VHO, which is capable of combining the merits of both schemes to achieve excellent handover in terms of packet transfer delay for all the cases considered here. The strength of FL in handling uncertain and conflicting decision metrics is exploited. Since excessive transfer delay results in disrupted connection and corrupted service, the proposed FL-based VHO decision-making algorithm has the potential to provide a better quality of service (QoS) to users in future wireless broadband communications.     

A knowledge-based system for breast cancer classification using fuzzy logic method

Breast cancer has become a common disease around the world. Expert systems are valuable tools that have been successful for the disease diagnosis. In this research, we accordingly develop a new knowledge-based system for classification of breast cancer disease using clustering, noise removal, and classification techniques. Expectation Maximization (EM) is used as a clustering method to cluster the data in similar groups. We then use Classification and Regression Trees (CART) to generate the fuzzy rules to be used for the classification of breast cancer disease in the knowledge-based system of fuzzy rule-based reasoning method. To overcome the multi-collinearity issue, we incorporate Principal Component Analysis (PCA) in the proposed knowledge-based system. Experimental results on Wisconsin Diagnostic Breast Cancer and Mammographic mass datasets show that proposed methods remarkably improves the prediction accuracy of breast cancer. The proposed knowledge-based system can be used as a clinical decision support system to assist medical practitioners in the healthcare practice.     

Connection admission control in ATM networks using survey-based type-2 fuzzy logic systems

This paper presents a connection admission control (CAC) method that uses a type-2 fuzzy logic system (FLS). Type-2 FLSs can handle linguistic uncertainties. The linguistic knowledge about CAC is obtained from 30 computer network experts. A methodology for representing the linguistic knowledge using type-2 membership functions and processing surveys using type-2 FLS is proposed. The type-2 FLS provides soft decision boundaries, whereas a type-1 FLS provides a hard decision boundary. The soft decision boundaries can coordinate the cell loss ratio (CLR) and bandwidth utilization, which is impossible for the hard decision boundary.     

Pedestrian trajectory prediction in crossing scenario using fuzzy logic and switching Kalman filter

Pedestrian trajectory prediction plays an important role in bothadvanced driving assistance system (ADAS) and autonomous vehicles. An algorithm for pedestrian trajectory prediction in crossing scenario is proposed. To obtain features of pedestrian motion, we develop a method for data labelling and pedestrian body orientation regression. Using the hierarchical features as domain of discourse, fuzzy logic rules are built to describe the transition between different pedestrian states and motion models. With derived probability of each type of motion model we further predict the pedestrian trajectory in the next 1.5 s using switching Kalman filter (KF). The proposed algorithm is further verified in our dataset, and the result indicates that the proposed algorithm successfully predicts pedestrian' s crossing behavior 0.4 s earlier before pedestrian moves. Meanwhile, the precision of predicted trajectory surpasses other methods including interacting multi-model KF and dynamic Bayesian network (DBN).     

On using fuzzy logic to integrate learning mechanisms in an electro-hydraulic system. I. Actuator's fuzzy modeling

Drive systems are usually modeled using a mathematical characterization of their physical phenomena. However, the difficulty in establishing a relevant model representation, in particular for electro-hydraulic systems, makes important the search for other modeling mechanisms that allow the combination of previously compiled system's knowledge with acquired experimental information. This paper, divided into two parts, describes the potential and possible drawbacks of integrating fuzzy learning mechanisms into a drive system that includes an electro-hydraulic actuator. First, experimental verification of the actuator's fuzzy modeling is presented in Part I of the paper, where the variable selection problem and the performance of the learning algorithm are discussed. In Part II, extensive experimental results employing the extracted fuzzy model and associated learning algorithm are presented. The feasibility and effectiveness of integrating fuzzy learning mechanisms into the actuator's control is also discussed.     

组合ZnS双稳器件的光学多稳性与多值逻辑运算

运用ZnS干涉滤光片双稳器件的组合,实现了光学多稳态及三值逻辑门。这种器件具有制作工艺简单、阈值功率低和可室温运转等特点,是进行光计算回路可行性研究的理想元件。     

一种模糊时态描述逻辑

针对现实生活中信息的时间性和模糊性,在模糊描述逻辑和时态逻辑的基础上,提出了一种模糊时态描述逻辑FTDL,并给出了其语法和语义的相关说明。与模糊描述逻辑FALC相比,FTDL的提出为语义Web服务的建模和推理提供了一种有效的途径。     

光电子混合模糊逻辑

本文提出了一种由光电子混合回路构成的简单光学模糊逻辑门设计。演示了补、最大、最小和限界差(相对补)四种最基本的逻辑操作。给出了一个多功能可编程的光电子混合模糊逻辑门,可实现模糊逻辑中七种基本逻辑运算。