• 한국수학교육학회지시리즈B:순수및응용수학
• /
• 제28권4호
• /
• pp.281-296
• /
• 2021

In this paper, we suggest a representation for an inverse transform of the generalized Fourier-Feynman transform on the function space C_a,b[0, T]. The function space C_a,b[0, T] is induced by the generalized Brownian motion process with mean function a(t) and variance function b(t). To do this, we study the generalized Fourier-Feynman transform associated with the Gaussian process Ƶ_k of exponential-type functionals. We then establish that a composition of the Ƶ_k-generalized Fourier-Feynman transforms acts like an inverse generalized Fourier-Feynman transform.

• 한국음향학회지
• /
• 제18권7호
• /
• pp.112-117
• /
• 1999

잡음에 강한 음성인식시스템을 위하여 주파수 차감법을 사용할 경우 음성 신호마저 차감하여 신호를 더욱 부식시키는 경우가 존재한다. 본 연구에서는 이러한 경우를 위해서 프레임 마다 추정 잡음과 차감 신호의 SNR(Signal to Noise Ratio) 함수로부터 반연속 HMM(Hidden Markov Model)의 가우시안 함수를 변형 및 결정하는 방법을 제안한다. 이 방법의 타당성을 위해 프레임마다 추정 잡음의 오류 정도가 추정 잡음의 크기와 관계함을 신호 파형 형태로써 보였으며, 이러한 이유에서 SNR을 기준으로 가우시안 함수를 변형 및 결정하게 된다. 실험에서 80㎞/h 이상의 속도로 달리는 차량 내에서 배경 잡음과 음성이 혼합되었을 때의 음성 인식율을 평가하였다. 그 결과 주파수 차감한 경우와 차감하지 않은 경우에 비해 본 논문에서 제안한 SNR에 의한 가우시안 결정 방법이 더욱 향상된 인식율을 보였다.

• 한국정보통신학회논문지
• /
• 제17권6호
• /
• pp.1409-1413
• /
• 2013

본 연구에서는 이중게이트 MOSFET의 채널도핑농도의 변화에 따른 문턱전압이하 전류의 변화를 분석하였다. 이를 위하여 이중게이트 MOSFET의 채널 내 전위분포를 구하기 위하여 포아송방정식을 이용하였으며 이때 전하분포함수에 대하여 가우시안 함수를 사용하였다. 전위분포는 경계조건을 이용하여 채널크기에 따른 해석학적인 함수로 구하였다. 가우시안 함수의 변수인 이온주입범위 및 분포편차 그리고 채널도핑농도 등에 대하여 문턱전압 이하 전류 특성의 변화를 관찰하였다. 본 연구의 전위모델에 대한 타당성은 이미 기존에 발표된 논문에서 입증하였으며 본 연구에서는 이 모델을 이용하여 문턱전압이하 전류 특성을 분석하였다. 분석결과, 문턱전압이하 전류는 채널도핑농도 및 가우시안 분포함수의 변수 등에 크게 영향을 받는 것을 관찰할 수 있었다.

• Journal of applied mathematics & informatics
• /
• 제20권1_2호
• /
• pp.585-594
• /
• 2006

We consider a stochastic integral process represented by multiple Ito-Wiener integrals. We derive gaussian chaos which has some shift continuous function. We get continuity property of self-similar process represented by multiple integrals and finally we show that $Y_{H_t}$ (t) is continuous in t with probability one for Holder function $H_t$ of exponent $\beta$.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (C)
• /
• pp.485-489
• /
• 2007

Gaussian process classifiers (GPCs) are fully statistical kernel classification models which have a latent function with Gaussian process prior Recently, EP approximation method has been proposed to infer the posterior over the latent function. It can have a special hyperparameter which can treat outliers potentially. In this paper, we propose the outlier robust algorithm which alternates EP and the hyperparameter updating until convergence. We also show its usefulness with the simulation results.

• ETRI Journal
• /
• 제33권6호
• /
• pp.949-952
• /
• 2011

In this letter, a simplified suboptimum receiver based on soft-limiting for the detection of binary antipodal signals in non-Gaussian noise modeled as a generalized normal-Laplace (GNL) distribution combined with Gaussian noise is presented. The suboptimum receiver has low computational complexity. Furthermore, when the number of diversity branches is small, its performance is very close to that of the Neyman-Pearson optimum receiver based on the probability density function obtained by the Fourier inversion of the characteristic function of the GNL-plus-Gaussian distribution.

• 제어로봇시스템학회논문지
• /
• 제11권12호
• /
• pp.991-995
• /
• 2005

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as health, environment and habitat monitoring, military, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modern teaming techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes haying the capability of simple processing and wireless communication. The proposed system is able to perform classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to hand gesture recognition system.

• 대한수학회보
• /
• 제54권3호
• /
• pp.789-797
• /
• 2017

The main purpose of this paper is to present closed integral form expressions for the Mathieu-type a-series and its associated alternating version whose terms contain a (p, q)-extended Gauss' hypergeometric function. Certain upper bounds for the two series are also given.

• Journal of the Korean Statistical Society
• /
• 제26권1호
• /
• pp.57-74
• /
• 1997

Csorgo-Revesz type theorems for Wiener process are developed to those for Gaussian process. In particular, some results of superior and inferior limits for the increments of a Gaussian process are differently obtained under mild conditions, via estimating probability inequalities on the suprema of a Gaussian process.

• 소음진동
• /
• 제10권5호
• /
• pp.769-774
• /
• 2000

The purpose of the work is to present successful applications of a modified wavelet shrinkage method for the accurate and fast estimation of a transfer function. Although the experimental process of determining a transfer function introduces not only Gaussian but also non-Gaussian noises, most existing estimation methods are based only on a Gaussian noise model. To overcome this limitation, we propose to employ a modified wavelet shrinkage method in which L1 -based median filtering and L2 -based wavelet shrinkage are applied repeatedly. The underlying theory behind this approach is briefly explained and the superior performance of this modified wavelet shrinkage technique is demonstrated by a numerical example.