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An Affine Projection Algorithm Based on Reuse Time of Input Vectors
MoonSoo Chang,NamWoong Kong,PooGyeon Park IEEE 2010 IEEE signal processing letters Vol.17 No.8
<P>This letter proposes an affine projection algorithm (APA) based on the concept of reuse time of the current input vector. Reuse time is defined as the survival period of an input vector, during which the input vector is continuously reused in the subsequent update equations. The algorithm consists of two key procedures: assignment and reduction. The assignment procedure assigns a fundamental reuse-time or zero to the individual reuse time of each current input vector only once by checking whether the current input vector has enough information for update, which eliminates the repetitive selection procedure for input vectors. The reduction procedure gradually decreases the fundamental reuse time by examining, from a stochastic point of view, whether the current error reaches the steady-state value, which indirectly controls the number of input vectors; this leads to fast convergence and small estimation errors. Through these two procedures, the proposed algorithm achieves not only improved performance but also extremely low computational complexity.</P>
장문수(Moonsoo Chang),강선미(Sunmee Kang) 한국음성학회 2007 음성과학 Vol.14 No.4
This thesis describes the development of a service system for small-sized shops which support not only music broadcasting, but editing and generating voice announcement using the TTS(Text-To-Speech) technology. The system has been developed based on web environments with an easy access whenever and wherever it is needed. The system is able to control the sound using silverlight media player based on the ASP .NET 2.0 technology without any additional application software. Use of the Ajax control allows for multiple users to get the maximum load when needed. TTS is built in the server side so that the service can be provided without user's computer. Due to convenience and usefulness of the system, the business sector can provide better service to many shops. Further additional functions such as statistical analysis will undoubtedly help shop management provide desirable services.
녹음 환경의 차이에 따른 화자의 음원 특성 비교 : 발성유형지수 k를 중심으로
이후동,강선미,박한상,장문수 한국음성과학회 2003 음성과학 Vol.10 No.3
Spoken sound includes not only speaker's source but the characteristics of vocal tract and speech radiation. This paper is based on the theory of Park[1], who proposes the Phonation Type Index k; a variable that shows the characterisic of speaker's source excluding those of speaker's vocal tract and speech radiation. With Park's theory, we collect data by changing recording environments and expanding experimental data, and analyze the data collected to see whether or not the PTI k shows good discriminating power as a variable for speaker recognition. In the experiment, we repeatedly record 8 sentences ten times for each of 5 males in the environment of a recording room and an office, extract PTI k for each speaker, and measure the discriminating power for each speaker by using the value of PTI k. The result shows that PTI k has the excellent discriminating power of speakers. We also confirm that, even if the recording environment is changed, PTI k shows similar results.
Scheduled-Stepsize NLMS Algorithm
Poogyeon Park,Moonsoo Chang,Namwoong Kong IEEE 2009 IEEE signal processing letters Vol.16 No.12
<P>This paper presents a method of scheduling stepsizes for the normalized least-mean-squares (SS-NLMS) algorithm. Geometrically interpreting the mean square deviation (MSD) learning curve leads to establishing an objective curve and to constructing a lookup table of stepsizes in order for the MSD to follow the curve. The SS-NLMS shows not only good performance but also robustness with respect to different signal-to-noise ratio (SNR) in measurement noise and different correlation in input signals with a very small number of online computations. Moreover, the scalability of the tabled stepsize with respect to the number of taps is described. For the efficient memory usage in practice, a modified version replaces the tabled stepsizes by down-sampled stepsizes with no performance degradation.</P>
장성호(Sung-Ho Chang),권문수(Moonsoo Kwon),김근태(Geuntae Kim),이종환(Jonghwan Lee) 한국산업경영시스템학회 2021 한국산업경영시스템학회지 Vol.44 No.2
Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.
New Algorithm of Localization Using Odometry and RFID System
이규민(Gyumin Lee),장문수(Moonsoo Chang),박부견(Poogyeon Park) 대한전기학회 2008 대한전기학회 학술대회 논문집 Vol.2008 No.10
Localization and its applications are very important area of the mobile robot technology. Especially, accurate localization is needed when we move the mobile robot to the goal position. In indoor cases. Global Positioning System(GPS) is not suitable but Radio Frequency Identification(RFID) technology can provide position data to the robot. A proposed algorithm in this paper uses not only odometry data but also RFID data to improve estimation of true position of the robot with the particle filtering.