Journal of Intelligent & Fuzzy Systems - Volume 36, issue 3

Authors: Chopra, Parul | Agarwal, Shivangi | Rani, Asha | Singh, Vijander

Article Type: Research Article

Abstract: A myoelectric prosthetic limb can be directed by sEMG signals from amputee’s residual muscles. The capability of such prosthetic hand may be enhanced by classifying additional hand motion commands. As the amputee’s residual muscles are limited and it is essential to come up with the ways to identify as many hand motion directions as possible with sEMG signals recognized by few sensors. Recent algorithms for pattern recognition in sEMG signals are tested with limited recognition patterns and inconsistent classification accuracy. The proper choice of denoising algorithm has intense effect on classification rates. Therefore FIR-median hybrid (FMH) filter, and discrete wavelet …transform (DWT) denoising methods are used in this work for filtering sEMG signals. Five time domain features are used for classification of motions and four different physical activities are classified using ANN. It is observed from the results that FMH filter removes noise more effectively as compared to DWT which improves the classification accuracy. Show more

Keywords: sEMG, DWT, FMH, LM-Backpropogation algorithm, physical action classification, myoelectric prosthetic limb

DOI: 10.3233/JIFS-169924

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2125-2135, 2019

Authors: Bhavanam, Srinadh Reddy | R V, Sanjika Devi | Mudulodu, Sriram | Kurup, Dhanesh G.

Article Type: Research Article

Abstract: This article presents a novel information criterion based optimal model parameter selection algorithm for behavioral modeling of Radio Frequency Power Amplifiers (RF PAs). The proposed approach uses Particle Swarm Optimization (PSO) along with the Information Criterion (IC) based cost functions for determining the most parsimonious model from all the available combinatorial models. The proposed technique thereby helps in deriving complexity reduced models without compromising modeling accuracy. The validation of the proposed approach was carried out by modeling a GaAs based PA driven by a 20-MHz generic random input signal. It was shown that, the model performance was maintained while its …complexity in terms of number of coefficients was reduced by around 35% in the considered cases. In addition, the proposed PSO based approach helps in deriving the most parsimonious PA model in a very short amount of time compared to the conventional sweep technique. Show more

Keywords: RF Power amplifiers, particle swarm optimization (PSO), information criterion (IC), maximum entropy (ME)

DOI: 10.3233/JIFS-169925

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2137-2145, 2019

Authors: Murali Krishna, P. | Pradeep Reddy, R. | Narayanan, Veena | Lalitha, S. | Gupta, Deepa

Article Type: Research Article

Abstract: This paper presents a technique to detect the six affective states of individual using audio cues. Bi-spectral features extracted from entire speech signal and voiced part of speech are used to create feature vectors. For classification K-Nearest Neighbor (KNN) and Simple Logistic Classifiers (SL) are used. eNTERFACE audio-visual emotional speech corpus that consists of six archetypal affective states: Fear, Anger, Disgust, Sad, Happy, and Surprise is considered. The performance of the system is analyzed based on features obtained from voiced part of speech and features obtained from the entire speech signal. The work proposed is first of its kind …in affect computation, where a compact 13-dimensional Bi-spectral features extracted from the voiced speech segments is able to yield promising performance. A considerable improvement of 8.46% – 27.6% recognition rate is achieved with the proposed methodology compared to the existing approaches using emotion samples from the same speech corpus adding novelty to the proposed work. Show more

Keywords: Bi-spectral, voiced speech, affective state recognition

DOI: 10.3233/JIFS-169926

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2147-2154, 2019

Authors: Laskar, Mohammad Azharuddin | Laskar, Rabul Hussain

Article Type: Research Article

Abstract: In recent times, Dynamic Time Warping (DTW) based template matching systems have again come to the forefront in the field of text-dependent speaker verification. Its integration with the latest technology, like i-vector/Probabilistic Linear Discriminant Analysis (PLDA) and Deep Neural Network (DNN), has resulted in significant improvement in the performance of the systems. DTW algorithm time-aligns two templates and gives a similarity score based on the optimal warping path. It however weighs all the local distances equally, along the optimal path. In this paper, we propose complementing the DTW based text-dependent speaker verification systems with local scores derived from the vicinity …of speaker-identity-rich regions. The vowel regions are used to determine portions along the warping path that are more important in terms of speaker discriminating information content. Two systems, namely the DTW/ Mel-frequency Cepstral Coefficients (MFCC) system and the online i-vector/PLDA/DTW system have been extended to incorporate the knowledge of specific regions of interest. The results have been evaluated on Part 1 of RSR2015 database. Relative improvements of upto 11.85% and 49.41% are observed for the extended systems based on MFCC and i-vector respectively. Show more

Keywords: DTW, vowel regions, online i-vector, text-dependent speaker verification

DOI: 10.3233/JIFS-169927

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2155-2163, 2019

Authors: Nangrani, S.P.

Article Type: Research Article

Abstract:  Small perturbations quite often lead to power system instability. Power system stabilizer damp the electro mechanical oscillations in generator. Design of power system stabilizer has changed over past few decades. Artificial intelligence based controllers are found to be more effective to handle complex control situations during perturbations in power system. Fuzzy logic supported power system stabilizers were proposed to control such perturbations in more efficient way than conventional one. Fractional order controllers perform better than their counterparts in various engineering applications. This paper suggests use of such state of art fractional order controller in conjunction with existing power system stabilizer …to enhance performance in terms of damping of electromechanical oscillations. From the results obtained from simulation models, it is observed that judicious design of fractional order controller in power system gives better handling of control operations. Comparison of conventional, fuzzy based and Fractional Order based power system stabilizer reveals usefulness of proposed controller. Show more

Keywords: Power system stabilizer, fractional order power system stabilizer, fuzzy power system stabilizer

DOI: 10.3233/JIFS-169928

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2165-2173, 2019

Authors: Chauhan, Urvashi | Rani, Asha | Kumar, Bhavnesh | Singh, Vijander

Article Type: Research Article

Abstract:  This paper proposes Multi verse optimization (MVO) based MPPT controller to mitigate the possibility of losing tracking direction in solar photovoltaic system under variable irradiance. Generally conventional Perturb & Observe and hill climbing MPPT techniques are used due to effortless implementation. However, these techniques are not capable of handling oscillations in power at MPP and exhibit drift under variable irradiance conditions which leads to power loss. Therefore a hybrid of standard MVO and direct duty cycle control is proposed to minimize the inadequacies occurring in conventional controllers. Three cases i.e. constant irradiance, rapid and step changes in irradiance are …considered for the analysis. The supremacy of proposed method is justified by comparing it with traditional P&O, Particle swarm optimization (PSO) based MPPT and Grey wolf optimization (GWO) based MPPT techniques. It is observed from the results that MVO based MPPT controller is capable of avoiding drift and offers fast convergence. Therefore proposed controller outperforms in terms of tracking efficiency, settling time, peak overshoot, and integral absolute error. Show more

Keywords: Solar PV system, MPPT, optimization technique, multi verse optimization

DOI: 10.3233/JIFS-169929

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2175-2184, 2019

Authors: Singh, Arunesh Kumar | Nasiruddin, Ibraheem | Sharma, Amit Kumar | Saxena, Abhinav

Article Type: Research Article

Abstract: Combination of conventional brakes with Eddy Current Brake is the current trend in many applications where superior braking performance at high speed is desired. Eddy Current Brakes being frictionless and contactless offer numerous advantages over conventional brakes. This paper gives detailed insight into the hardware model development, analysis and control of a multi disc Eddy Current Braking System using different intelligent controllers. Firstly, Fuzzy Logic Controller has been developed which can give the feasible value of the electromagnet current required which leads to improved braking performance. Further, Artificial Neural Network Controller has been designed for existing hardware system which gives …better, reliable, efficient results in comparison to the Fuzzy Logic Controller and hardware reference model for the sample period of time. Show more

Keywords: Artificial neural network, braking torque, eddy current brake, fuzzy controller, modelling, response time

DOI: 10.3233/JIFS-169930

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2185-2194, 2019

Authors: Chhabra, Himanshu | Mohan, Vijay | Rani, Asha | Singh, Vijander

Article Type: Research Article

Abstract:  Stability of a parallel manipulator is a very important issue due to its high nonlinearity and vague dynamics. This problem may be overcome by a controller, based on the combination of Lyapunov theory and fuzzy logic. In this paper a novel linguistic Lyapunov based fuzzy controller (LLFC) is proposed in which fuzzy logic controller improves trajectory tracking performance of parallel manipulator and application of Lyapunov theory provides stable control action. The subsequent part of rule base in fuzzy controller is constrained by Lyapunov criteria so as to generate a control action which stabilizes the system. Non dominated sorting genetic algorithm–II …(NSGA-II) optimization technique is used to evaluate the optimal values of controller parameters. The effectiveness of proposed LLFC controller is tested on Maryland manipulator and compared with PID, Fractional order PID (FOPID) and Fractional order fuzzy pre-compensated fractional order PID (FOFP FOPID) controllers. Simulation results reveal that the proposed controller shows stable, robust and better tracking performance for Maryland manipulator in comparison to PID, FOPID and FOFP FOPID controllers. Show more

Keywords: LLFC, NSGA-II, maryland manipulator, fuzzy logic control

DOI: 10.3233/JIFS-169931

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2195-2205, 2019

Authors: Bhanja, Chuya China | Bisharad, Dipjyoti | Laskar, Rabul Hussain

Article Type: Research Article

Abstract:  This paper proposes a pre-classification based language identification (LID) system for Indian languages. In this system, firstly, languages are pre-classified into tonal and non-tonal categories and then individual languages are identified from the languages of the respective category. In this work, language discriminating ability of various acoustic features like, pitch Chroma, mel-frequency Cepstral coefficients (MFCCs) and their combination has been investigated. The system performance has been analyzed for features extracted using different analysis units, like, syllables and utterances. The effectiveness of deep residual networks (ResNets) model in identification of Indian languages has been studied. Also, the system performance has been …compared with the performances of other deep neural network architectures like, Convolutional Neural network (CNN) model, cascade CNN-long short-term memory (LSTM) model and shallow architecture like, ANN. Experiments have been carried out on NIT Silchar language database (NITS-LD) and OGI-Multilingual database (OGI-MLTS). Experimental analysis suggests that proposed ResNets model, based on syllable-level features, outperforms the other models. The pre-classification module provides accuracies of 96.6%, 93.2% and 90.6% for NITS-LD, and 92.1%, 89.3% and 85.4% for OGI-MLTS database, with 30s, 10s and 3s test data respectively. The pre-classification module helps to improve the system performance by 3.8%, 4.1% and 4.3% for 30s, 10s and 3s test data respectively. For OGI-MLTS database, the respective improvements are 6.8%, 6.5% and 5.4%. Show more

Keywords: Language identification, tonal and non-tonal languages, ResNets, Chroma and MFCC, NITS-LD

DOI: 10.3233/JIFS-169932

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2207-2218, 2019

Authors: Sharma, Vijay | Mittal, Namita

Article Type: Research Article

Abstract:  Cross-Lingual Information Retrieval (CLIR) enables a user to query in a language which is different than the target documents language. CLIR incorporates a machine translation technique, like, Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) which use either a dictionary or a parallel corpus for the training. A Hindi language word may have multiple variations due to the morphological richness of the language, these morphological variants may or may not be present in the dictionary or parallel corpus. The morphological variants which are not present in the dictionary or parallel corpus, are not translated by the state-of-art SMT or …NMT translation techniques. Conventional Information Retrieval (IR) technique eliminates the stop-words to improve the IR effectiveness, but there are some significant stop-words whose presence may improve the IR effectiveness. In this paper, a translation induction algorithm, incorporates the refined stop-words list, morphological variants solutions, and translates the words based on the contextual words, is proposed. The proposed algorithm is compared to the manual dictionary, probabilistic dictionary, SMT and NMT based translation techniques for the experimental analysis of Hindi-English CLIR, where it outperforms the other CLIR approaches. Show more

Keywords: Cross-lingual information retrieval, refined stop-words, morphological variants solutions, statistical machine translation, neural machine translation

DOI: 10.3233/JIFS-169933

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2219-2227, 2019