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Adaptive Morse code communication system for severely disabled individuals

MEDICAL ENGINEERING & PHYSICS 2000年第1期22卷 59-66页

作者： Yang, CH Natl Kaohsiung Inst Technol Dept Elect Engn Kaohsiung Taiwan

Morse code with an easy-to-operate, single switch input system has been shown to be an excellent communication adaptive device. Because maintaining a stable typing rate is not easy for the disabled, the automatic recognition of Morse code is difficult. Therefore, a suitable adaptive automatic recognition method is needed. This paper presents the application of a least-mean-square algorithm to adaptive Morse code recognition for persons with impaired hand coordination and dexterity. Four processes are involved in this adaptive Morse code recognition method: space recognition, tone recognition, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method results in a better recognition rate for the participants tested in comparison to other methods from the literature. (C) IPEM. Published by Elsevier Science Ltd. All rights reserved.

关键词： Morse code adaptive signal processing least-mean-square algorithm Friedman test multiple comparison test

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Adaptive decision-feedback generalised sidelobe canceller against desired signal and interference non-stationarity

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IET SIGNAL PROCESSING 2011年第5期5卷 488-498页

作者： Lee, Y. Shieh, H. -W. Natl Chi Nan Univ Grad Inst Commun Engn Puli Nantou County Taiwan

Adaptive generalised sidelobe canceller (GSC) implemented with the least-mean-square (LMS) algorithm is a well-proven approach to effectively suppress unwanted interference. However, when the directions-of-arrival (DOAs) of the desired signal and interference sources change over time, its performance may be largely degraded because of the fact that not only the interference-cancelling filter of GSC does not properly cancel the 'moving' interference, but also both the signal-matched filter and blocking matrix of GSC deviate from their best states for the 'moving' desired signal. Recently, a robust adaptive decision-feedback (DF) GSC has been proposed to partly solve the problem, but if the DOAs of all sources vary significantly and continuously, the adaptive DFGSC will eventually lose track of the source motion. In this study, the authors present a new modification for the DFGSC structure, which provides additional robustness in this kind of non-stationary signal environment. Specifically, they extend the use of Householder transformation together with the LMS algorithm for DFGSC, and a new update method is introduced for the whole beamforming processor. In addition, the tracking behaviour of this specially designed adaptive structure is studied and analysed, leading to the derivation of optimal step size for the interference-cancelling filter. Simulation results show that this modified adaptive DFGSC is very effective in mitigating the described non-stationary scenario.

关键词： adaptive decision-feedback generalised sidelobe canceller Electromagnetic compatibility and interference householder transformation Filtering methods in signal processing Interpolation and function approximation (numerical analysis) interference non-stationarity directions-of-arrival blocking matrix interference suppression interference-cancelling filter signal-matched filter least-mean-square algorithm source motion matched filters beamforming processor direction-of-arrival estimation least mean squares methods adaptive generalised sidelobe canceller

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Fuzzy support vector machines for adaptive Morse code recognition

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MEDICAL ENGINEERING & PHYSICS 2006年第9期28卷 925-931页

作者： Yang, Cheng-Hong Jin, Li-Cheng Chuang, Li-Yeh Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 807 Taiwan I Shou Univ Dept Chem Engn Kaohsiung 807 Taiwan

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature. (c) 2006 IPEM. Published by Elsevier Ltd. All rights reserved.

关键词： Morse code least-mean-square algorithm support vector machines fuzzy theory

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A wireless internet interface for person with physical disability

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MATHEMATICAL AND COMPUTER MODELLING 2009年第1-2期50卷 72-80页

作者： Yang, Cheng-San Yang, Cheng-Huei Chuang, Li-Yeh Yang, Cheng-Hong Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 807 Taiwan Chiayi Christian Hosp Dept Phys Med & Rehabil Chiayi Taiwan Natl Kaohsiung Marine Univ Dept Elect Commun Engn Kaohsiung Taiwan I Shou Univ Dept Chem Engn Kaohsiung Taiwan

Technologically assistive devices are increasingly playing more important roles in the lives of persons with disabilities, with one of the more promising considerations being a combination of the functions of computer software and hardware. However, using a conventional keyboard for Internet access is prohibitive for persons whose hand coordination and dexterity are impaired by ailments such as amyotrophic lateral sclerosis, multiple sclerosis, muscular dystrophy, and other severe handicaps. To assist participants with physical disabilities in sharing the resources of the Internet, we designed and implemented an easy-to-operate wireless input interface using Morse code as an adaptive communication tool. Moreover, an adaptive Morse code recognition process is introduced. After two months' practice on this system, three participants with physical disabilities could conveniently gain access to the Internet. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Morse code Adaptive signal processing WWW Internet least-mean-square algorithm

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Distributed Estimation with Novel Adaptive Data Selection Based on a Cross-Matching Mechanism

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第10期42卷 6324-6346页

作者： Wan, Fangyi Hua, Yi Liao, Bin Ma, Ting Qing, Xinlin Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China Xiamen Univ Sch Aerosp Engn Xiamen 361000 Peoples R China

Distributed estimation using general data selection (DS) has always been applicable for reducing calculation loads in many fields. However, the traditional general DS (GDS) mode can deteriorate algorithm performance and usually neglects solving the problem of communication cost. These issues arise because distributed estimation is extremely susceptible to selecting the fused data and requires swapping all data. To solve these problems, a diffusion least-mean-square (DLMS) algorithm with an adaptive DS (ADS) is proposed to improve the GDS mode. The proposed algorithm can choose more reliable information in the data fusion process and diminish the communication cost (by using the saved intermediate data of previous iteration) and the calculation load. In addition, in GDS mode, the DS factor (DSF) selects data based on noise statistics (NS), resulting in some loss of selection ability. To further improve this situation, a novel cross-matching mechanism is proposed to improve the design of the DSF based on an intermediate estimation error. The mean stability and mean-square performance of the proposed DLMS algorithm with the ADS mode are analyzed theoretically, which can derive a convergence condition based on the step-size. Theoretical verification and target localization simulations are implemented to illustrate the effectiveness and robustness of the proposed ADS algorithm under satisfying the convergence condition as compared to other related DS algorithms.

关键词： Adaptive data selection Distributed estimation least-mean-square algorithm Cross-matching mechanism

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LMSK: a robust higher-order gradient-based adaptive algorithm

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IET SIGNAL PROCESSING 2019年第5期13卷 506-515页

作者： Eghbal, Meysam Kazemi Alipoor, Ghasem Hamedan Univ Technol Elect Engn Dept Shahid Fahmideh Blvd Hamadan Iran

It has been shown that, in intensely noisy environments, adaptive algorithms based on higher-order statistics can enjoy better performance, as compared with the well known second-order least-mean-square (LMS) algorithm. By contrast, this advantage diminishes for low signal-to-noise ratio (SNR) levels, where the LMS algorithm outperforms. One remedy is to employ the LMS algorithm in conjunction with a higher-order adaptation algorithm, in a mixed mode. least-mean kurtosis (LMK) is a higher-order algorithm that has been shown to be advantageous to use if the noise distribution is Gaussian or super-Gaussian. In this study, the authors propose the LMS/kurtosis algorithm, a stochastic gradient-based adaptive algorithm that is a combination of the LMS and the LMK algorithms. Simulation results demonstrate the privilege of the proposed algorithm, in comparison with its counterparts, for a wide range of noise distributions and SNR levels. This improvement is achieved in spite of a negligible increase in computational complexity. An analytical model is also derived for the mean weight as well as the weight-error covariance matrix, from which the mean-square-error behaviour of the algorithm can be predicted. Simulation results show the high accuracy of the derived model in different conditions.

关键词： least mean squares methods higher order statistics gradient methods stochastic processes adaptive filters computational complexity filtering theory covariance matrices mean-square-error behaviour higher-order gradient-based adaptive algorithm intensely noisy environments adaptive algorithms higher-order statistics least-mean-square algorithm low signal-to-noise ratio LMS algorithm outperforms higher-order adaptation algorithm least-mean kurtosis higher-order algorithm noise distribution LMS kurtosis algorithm stochastic gradient-based adaptive algorithm LMK algorithms

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A NEW LMS-BASED algorithm FOR RAPID ADAPTIVE CLASSIFICATION IN DYNAMIC ENVIRONMENTS

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NEURAL NETWORKS 1989年第3期2卷 215-228页

作者： NGUYEN, DD LEE, JSJ Boeing High Tech Center USA

We developed a new algorithm for supervised adaptive classifications with rapid incremental learning characteristics in dynamic environments. The new algorithm outperforms the Widrow-Hoff algorithm in applications where: (a) real-time response is required, (b) the classifer is subjected to repeated train-then-apply cycles, and (c) the class distributions may change dynamically. The algorithm introduces (a) a dynamic cluster center representation, (b) a “balancing training” strategy, and (c) look-ahead learning by guard bands. Computational overhead for the improved performance is not excessive and strategies are further devised to reduce the overall computational complexity. The new algorithm is benchmarked against the Widrow-Hoff algorithm working as a clutter rejection unit in a target tracking system. Performance is shown for three sets of FLIR image sequence. The new algorithm outperformed the Widrow-Hoff algorithm (in terms of reduced misclassifications, and missed and false target rates). The improvement in missed target rate is very dramatic. The results also show that the new algorithm is not sensitive to parameter-setting.

关键词： Adaptive classification Neural-based adaptation Supervised learning least-mean-square algorithm Balancing training Target tracking Clutter rejection Dynamic environments

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A Morse-code recognition system with LMS and matching algorithms for persons with disabilities

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 1997年第3期44卷 193-202页

作者： Shih, CH Luo, CH NATL CHENG KUNG UNIV DEPT ELECT ENGNTAINAN 70101TAIWAN

Single-switch communication is an effective auxiliary method for persons with disabilities. However, it is not easy to recognize the Morse codes typed by them. In our earlier proposed Morse code auto-recognition method, using the least-mean-square (LMS) adaptive algorithm, it was demonstrated that the system could successfully recognize the Morse-coded messages at unstable typing speeds. However, the speed variation had to be limited to a range between 0.67 and two times the present speed. In the case of beginners or those with heavy disabilities, this rule can not always be complied with, producing a low recognition rate of 20%. To address this limitation, this paper offers an advanced recognition method which combines the least-mean-square algorithm with a character-by-character matching technique. The recognition rate for this method from simulated and real data from various sources is as high as 75% or more on average. This practical application of the single-switch method means a step forward toward alternative communication for disabled persons. (C) 1997 Elsevier Science Ireland Ltd.

关键词： morse code adaptive signal processing least-mean-square algorithm matching

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Single switch Chinese phonetic communication system

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2002年第1期18卷 115-124页

作者： Yang, CH Yang, CH Chuang, LY Luo, CH Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 807 Taiwan Natl Kaohsiung Inst Marine Technol Dept Telecommun & Comp Engn Kaohsiung 811 Taiwan I Shou Univ Dept Chem Engn Kaohsiung 840 Taiwan Natl Cheng Kung Univ Dept Elect Engn Tainan 701 Taiwan

Morse code, with its single switch operation, has been shown to be an excellent adaptive communication device for the disabled, especially those with impaired hand coordination and dexterity. Because a stable typing rate is required for an accurate recognition of Morse code, it presents a major hindrance to disabled persons in applying Morse code as a useful communication tool. Therefore, a suitable adaptive recognition method is needed. This paper applies the least-mean-square algorithm to an adaptive Chinese phonetic Morse code recognition system which includes four processes: space recognition, tone recognition, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method results in a better recognition rate compared to alternative methods in the literature.

关键词： Morse code adaptive signal processing least-mean-square algorithm Friedman test multiple comparison test

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A new step-size searching algorithm based on fuzzy logic and neural networks for LMS adaptive beamforming systems

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2016年第5期24卷 4322-4338页

作者： Orozco-Tupacyupanqui, Walter Nakano-Miyatake, Mariko Perez-meana, Hector Inst Politecn Nacl Postgrad Sect Mech Elect Engn Mexico City 07738 DF Mexico

In this paper, a novel algorithm based on fuzzy logic and neural networks is proposed to find an approximation of the optimal step size mu for least-mean-squares (LMS) adaptive beamforming systems. A new error ensemble learning (EEL) curve is generated based on the final prediction value of the ensemble-average learning curve of the LMS adaptive algorithm. This information is classified and fed into a back propagation neural network, which automatically generates membership functions for a fuzzy inference system. An estimate of the optimal step size is obtained using a group of linguistic rules and the corresponding defuzzification method. Computer simulations show that a useful approximation of the optimal step size is obtained under different signal-to-noise plus interference ratios. The results are also compared with data obtained from a statistical analysis performed on the EEL curve. As a result of this application, a better mean square -error is observed during the training process of the adaptive array beamforming system, and a higher directivity is achieved in the radiation beam patterns.

关键词： Adaptive filtering adaptive beamforming neural-fuzzy systems least-mean-square algorithm membership functions

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