SAR Target Recognition Using Improved Fuzzy Neural Network

نویسندگان

  • Ling Mao
  • Mei Xie
  • Haitao Jia
چکیده

Target recognition in high-resolution synthetic aperture radar (SAR) images is a challenging task, because SAR images have higher ambiguity for different target, which will reduce the correct recognition rate. This paper presents an improved SAR recognition algorithm based on fuzzy neural network (FNN), which deals with the ambiguity SAR target recognition very well. This improved FNN system improves learning algorithm and structure which has fuzzy multi-input and fuzzy multi-output. This paper takes the MSTAR data as the test data in simulation to show that this improved fuzzy neural network obtains a higher correct recognition rate. Copyright © 2013 IFSA.

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

A new algorithm of SAR target recognition based on advance deep learning neural network

In order to improve the accuracy of synthetic aperture radar images target recognition, we have proposed a new algorithm of SAR target recognition based on advance Deep Learning neural network. The traditional radar recognition algorithm has many disadvantages, In order to improve the accuracy of synthetic aperture radar images target recognition, the author have proposed a new algorithm of SAR...

متن کامل

AN IMPROVED CONTROLLED CHAOTIC NEURAL NETWORK FOR PATTERN RECOGNITION

A sigmoid function is necessary for creation a chaotic neural network (CNN). In this paper, a new function for CNN is proposed that it can increase the speed of convergence. In the proposed method, we use a novel signal for controlling chaos. Both the theory analysis and computer simulation results show that the performance of CNN can be improved remarkably by using our method. By means of this...

متن کامل

Deep Learning for End-to-End Automatic Target Recognition from Synthetic Aperture Radar Imagery

The standard architecture of synthetic aperture radar (SAR) automatic target recognition (ATR) consists of three stages: detection, discrimination, and classification. In recent years, convolutional neural networks (CNNs) for SAR ATR have been proposed, but most of them classify target classes from a target chip extracted from SAR imagery, as a classification for the third stage of SAR ATR. In ...

متن کامل

Neural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten

Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...

متن کامل

An Improved Fuzzy Neural Network for Solving Uncertainty in Pattern Classification and Identification

Dealing with uncertainty is one of the most critical problems in complicatedpattern recognition subjects. In this paper, we modify the structure of a useful UnsupervisedFuzzy Neural Network (UFNN) of Kwan and Cai, and compose a new FNN with 6 types offuzzy neurons and its associated self organizing supervised learning algorithm. Thisimproved five-layer feed forward Supervised Fuzzy Neural Netwo...

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 2013