On the Smoothed Minimum Error Entropy Criterion
نویسندگان
چکیده
منابع مشابه
On the Smoothed Minimum Error Entropy Criterion
Recent studies suggest that the minimum error entropy (MEE) criterion can outperform the traditional mean square error criterion in supervised machine learning, especially in nonlinear and non-Gaussian situations. In practice, however, one has to estimate the error entropy from the samples since in general the analytical evaluation of error entropy is not possible. By the Parzen windowing appro...
متن کاملQuantized Minimum Error Entropy Criterion
Comparing with traditional learning criteria, such as mean square error (MSE), the minimum error entropy (MEE) criterion is superior in nonlinear and non-Gaussian signal processing and machine learning. The argument of the logarithm in Renyis entropy estimator, called information potential (IP), is a popular MEE cost in information theoretic learning (ITL). The computational complexity of IP is...
متن کاملLearning theory approach to minimum error entropy criterion
We consider the minimum error entropy (MEE) criterion and an empirical risk minimization learning algorithm when an approximation of Rényi’s entropy (of order 2) by Parzen windowing is minimized. This learning algorithm involves a Parzen windowing scaling parameter. We present a learning theory approach for this MEE algorithm in a regression setting when the scaling parameter is large. Consiste...
متن کاملAn Extended Result on the Optimal Estimation Under the Minimum Error Entropy Criterion
The minimum error entropy (MEE) criterion has been successfully used in fields such as parameter estimation, system identification and the supervised machine learning. There is in general no explicit expression for the optimal MEE estimate unless some constraints on the conditional distribution are imposed. A recent paper has proved that if the conditional density is conditionally symmetric and...
متن کاملISAR Image Improvement Using STFT Kernel Width Optimization Based On Minimum Entropy Criterion
Nowadays, Radar systems have many applications and radar imaging is one of the most important of these applications. Inverse Synthetic Aperture Radar (ISAR) is used to form an image from moving targets. Conventional methods use Fourier transform to retrieve Doppler information. However, because of maneuvering of the target, the Doppler spectrum becomes time-varying and the image is blurred. Joi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Entropy
سال: 2012
ISSN: 1099-4300
DOI: 10.3390/e14112311