Fuzzy Deconvolution of Hormone Time-Series

نویسنده

  • Piet Boekhoudt
چکیده

In this paper we describe a method to nd the Instantaneous Secretion Rate of a hormone. The dynamics of the relation between secretion rate and peripheral plasma hormone concentration is rst identiied by using learning signals. The fuzzy identii-cation method is based on fuzzy clustering and optimal output predefuzziication. The proposed method leads to a fuzzy inference system which is able to perform the decon-volution, i.e. reconstruction of the unknown secretion rate. The results compare well with other deconvolution methods.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fuzzy Deconvolution of Pulsatile Hormone Secretion

Hormone secretion is an intrinsically discontinuous process characterized by a pul-satile pattern. In this paper we describe a fuzzy deconvolution method for pulsatile hormone secretion signals. The secretion signal is modeled as a Poisson process. The fuzzy deconvolution method is based on fuzzy identiication by using learning signals, mountain clustering and optimal output predefuzziication. ...

متن کامل

A NEW APPROACH BASED ON OPTIMIZATION OF RATIO FOR SEASONAL FUZZY TIME SERIES

In recent years, many studies have been done on forecasting fuzzy time series. First-order fuzzy time series forecasting methods with first-order lagged variables and high-order fuzzy time series forecasting methods with consecutive lagged variables constitute the considerable part of these studies. However, these methods are not effective in forecasting fuzzy time series which contain seasonal...

متن کامل

Residual analysis using Fourier series transform in Fuzzy time series model

In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and Fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

متن کامل

Gyroscope Random Drift Modeling, using Neural Networks, Fuzzy Neural and Traditional Time- series Methods

In this paper statistical and time series models are used for determining the random drift of a dynamically Tuned Gyroscope (DTG). This drift is compensated with optimal predictive transfer function. Also nonlinear neural-network and fuzzy-neural models are investigated for prediction and compensation of the random drift. Finally the different models are compared together and their advantages a...

متن کامل

AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1995