HRR PROFILES TIME-FREQUENCY NON-NEGATIVE SPARSE CODING FOR SAR TARGET CLASSIFICATION
نویسندگان
چکیده
منابع مشابه
Non-negative sparse coding
Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this type of data representation and its relation to standard sparse coding and non-negative matrix factorization. We then give a simple yet efficient multiplicative algorithm for finding the optimal values of the hidden components...
متن کاملImproved Target Recognition and Target Detection Algorithms Using Hrr Profiles and Sar Images
In this thesis, a new algorithm to improve automatic target recognition techniques on High Range Resolution (HRR) Profiles is presented and also a number of ways are investigated for target detection using Synthetic Aperture Radar (SAR) images. A new 1-D hybrid Automatic Target Recognition (ATR) algorithm is developed for sequential High Range Resolution (HRR) radar signatures. The proposed hyb...
متن کاملFusion of HRR and SAR information for Automatic Target Recognition and Classification
This paper explores the fusion of moving High Range Resolution (HRR) and stationary Synthetic Aperture Radar (SAR) for automatic target recognition and classification. The tradeoffs of resolution and time-to-classify are investigated through simulation. By using a fusion approach, targets are effectively classified in a multitargetmultisensor scenario; however the Bayesian analysis does not acc...
متن کاملRice Classification and Quality Detection Based on Sparse Coding Technique
Classification of various rice types and determination of its quality is a major issue in the scientific and commercial fields associated with modern agriculture. In recent years, various image processing techniques are used to identify different types of agricultural products. There are also various color and texture-based features in order to achieve the desired results in this area. In this ...
متن کاملHeterogeneous Convolutive Non-Negative Sparse Coding
Convolutive non-negative matrix factorization (CNMF) and its sparse version, convolutive non-negative sparse coding (CNSC), exhibit great success in speech processing. A particular limitation of the current CNMF/CNSC approaches is that the convolution ranges of the bases in learning are identical, resulting in patterns covering the same time span. This is obvious unideal as most of sequential s...
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: Progress In Electromagnetics Research B
سال: 2014
ISSN: 1937-6472
DOI: 10.2528/pierb14040401