• Journal of Mechanical Science and Technology
• /
• v.20 no.6
• /
• pp.759-769
• /
• 2006

This paper proposes a new method of discretization for nonlinear systems using a Taylor series expansion and the zero-order hold assumption. The method is applied to sampled-data representations of nonlinear systems with input time delays. The delayed input varies in time and its amplitude is bounded. The maximum time-delayed input is assumed to be two sampling periods. The mathematical expressions of the discretization method are presented and the ability of the algorithm is tested using several examples. A computer simulation is used to demonstrate that the proposed algorithm accurately discretizes nonlinear systems with variable time-delayed inputs.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.23 no.5
• /
• pp.674-680
• /
• 1986

In this paper, a new design method for high density PLA by a simple row folding technique is proposed. The normal input line and its complement line of different two input lines are folded on the same row. Especially the only one input line pair of the different two input lines are folded by this method. Conseqently, the results of folding are better than those of conventional methods. An efficient technique of ordering columns is described. Also, constraints about outside circuitry are consideted in this algorithm. The proposed algorithm has been implemented on a personal computer by C language.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.35D no.2
• /
• pp.101-109
• /
• 1998

In this paper, we implemented holographic optical memory systm which can store and reconstruct many images using new input and angular multiplexing method. In the new input method, phase infomation of input image is inputed in the recording material instead of brightness information. To do so, we represented the images, which captured with CCD camera or displayed on the computer monitor, on the liquid crystal television(LCTV) which removed polarizer/analyzer. Therefore, we can generate uniform input beam intensity regardless of the total brightness of input image, and apply the scheduled recording method. Also we can increase the intensity of input beam so reduce the recording time of input image. And reconstructedimage is acquired by transforming phase information into brightness information of image with analyzer. The incident angle of reference beam is acquired by Fourier transform of the binary phase hologram(BPH) which designed with SA algorithm on the LCTV. The proposed optical memory system is stable because the incident angle of the reference beam is controlled easy and electronically. We demonstreated optical experiment which store and reconstruct various type images in BaTiO$_{3}$ using proposed holographic memory system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.04a
• /
• pp.297-300
• /
• 2005

In this study, we proposed genetically optimized self-organizing fuzzy polynomial neural network based on information granulation and evolutionary algorithm (gdSOFPNN), develop a comprehensive design methodology involving mechanisms of genetic optimization. The proposed gdSOFPNN gives rise to a structural Iy and parametrically optimized network through an optimal parameters design available within FPN (viz. the number of input variables, the order of the polynomial, input variables, the number of membership functions, and the apexes of membership function). Here, with the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The performance of the proposed gdSOFPNN is quantified through experimentation that exploits standard data already used in fuzzy modeling.

• Journal of Internet Computing and Services
• /
• v.2 no.3
• /
• pp.71-79
• /
• 2001

In Incremental attribute evaluation algorithm, a new input attribute is exact1y compared with a previous input attribute tree, and then determine which subtrees from the old should be used in constructing the new one. In this paper incremental attribute evaluation algorithm was used to make incremental evlauation of hierarchical attribute grammar more efficient1y, and reconstructing the incremental attribute evaluation algorithm by analyzing that of Carle and Pollock, finally the incremental attribute evaluation algorithm for optimalized attribute tree d' copy was constructed by applying element of attribute !ree dcopy to a new attribute tree d' copy. Also proving that how the reused nod and type of defined parameter in input program carried out the incremental attribute evaluation by using that algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.11A
• /
• pp.892-902
• /
• 2011

The opportunistic spatial orthogonalization (OSO) scheme, proposed by Cong Shen and Michael P. Fitz, allows the existence of secondary users during the period in which the primary user is occupying all licensed bands. This paper introduces an active secondary user selection algorithm which mitigates the interference from the primary user transmitter to the secondary user receiver based on single-input multi-output system without altering a primary user's transmission strategy. A proposed algorithm guarantees the minimum average throughput of the primary user and overcomes the average sum throughput of a conventional OSO. We have numerically analyzed the average throughput under various constraints.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.2
• /
• pp.280-286
• /
• 2013

In this paper, a noise reduction system is proposed for the speech interface in intelligent TV applications. To reduce TV speaker sound which are very serious noises degrading recognition performance, a noise reduction algorithm utilizing the direct TV sound as the reference noise input is implemented. In the proposed algorithm, transfer functions are estimated to compensate for the difference between the direct TV sound and that recorded with the microphone installed on the TV frame. Then, the noise power spectrum in the received signal is calculated to perform Wiener filter-based noise cancellation. Additionally, a postprocessing step is applied to reduce remaining noises. Experimental results show that the proposed algorithm shows 88% recognition rate for isolated Korean words at 5 dB input SNR.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.6
• /
• pp.70-75
• /
• 2000

This paper examines the performance of adaptive filtering algorithms in relation to the asymptotic relative efficiency (ARE) of estimators. The adaptive filtering algorithms are Hybrid II and modified zero forcing (MZF) algorithms. The Hybrid II and MZF algorithms are simplified forms of the LMS algorithm, which use the polarity of the input signal, and polarities of the error and input signals, respectively. The ARE of estimators for each algorithm is analyzed under the condition of the same convergence speed. Computer simulations for adaptive equalization are performed to check the validity of the theory. The explicit expressions for the ARE values of the Hybrid II and MZF algorithms are derived, and its results have similar values to the results of computer simulation. It also revealed that the ARE values depend on the correlation coefficients between input signal and error signal.

• Annual Conference of KIPS
• /
• 2002.04a
• /
• pp.647-650
• /
• 2002

The human faces do not have distinct features unlike other general objects. In general the features of eyes, nose and mouth which are first recognized when human being see the face are defined. These features have different characteristics depending on different human face. In this paper, We propose a face recognition algorithm using the hidden Markov model(HMM). In the preprocessing stage, we find edges of a face using the locally adaptive threshold scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability values calculated by the HMM to input data. Then the input face is recognized by the euclidean distance of face feature vector and the cross-correlation between the input image and the database image. Computer simulation shows that the proposed HMM algorithm gives higher recognition rate compared with conventional face recognition algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.471-473
• /
• 2009

In this paper, we propose a double talk and noise robust acoustic echo canceler for hands-free telephony applications. The proposed system includes a double-talk detection method that detects the double-talk durations, which uses covariance between microphone input signa and estimated microphone input signal. And proposed adaptive algorithm for estimating acoustic echo path, uses normalized auto-covariance matrix of input signal with multiplication of residual error power and projection order of AP(affine projeciton) algorithm. It is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint in double talk and noisy environments.