Next Issue
Previous Issue

Table of Contents

Algorithms, Volume 4, Issue 3 (September 2011), Pages 155-222

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-3
Export citation of selected articles as:

Research

Open AccessArticle Radio-Frequency Interference Detection and Mitigation Algorithms for Synthetic Aperture Radiometers
Algorithms 2011, 4(3), 155-182; doi:10.3390/a4030155
Received: 20 April 2011 / Revised: 15 July 2011 / Accepted: 11 August 2011 / Published: 30 August 2011
Cited by 13 | PDF Full-text (2677 KB) | HTML Full-text | XML Full-text
Abstract
The European Space Agency (ESA) successfully launched the Soil Moisture and Ocean Salinity (SMOS) mission in November 2, 2009. SMOS uses a new type of instrument, a synthetic aperture radiometer named MIRAS that provides full-polarimetric multi-angular L-band brightness temperatures, from which regular and
[...] Read more.
The European Space Agency (ESA) successfully launched the Soil Moisture and Ocean Salinity (SMOS) mission in November 2, 2009. SMOS uses a new type of instrument, a synthetic aperture radiometer named MIRAS that provides full-polarimetric multi-angular L-band brightness temperatures, from which regular and global maps of Sea Surface Salinity (SSS) and Soil Moisture (SM) are generated. Although SMOS operates in a restricted band (1400–1427 MHz), radio-frequency interference (RFI) appears in SMOS imagery in many areas of the world, and it is an important issue to be addressed for quality SSS and SM retrievals. The impact on SMOS imagery of a sinusoidal RFI source is reviewed, and the problem is illustrated with actual RFI encountered by SMOS. Two RFI detection and mitigation algorithms are developed (dual-polarization and full-polarimetric modes), the performance of the second one has been quantitatively evaluated in terms of probability of detection and false alarm (using a synthetic test scene), and results presented using real dual-polarization and full-polarimetric SMOS imagery. Finally, a statistical analysis of more than 13,000 L1b snap-shots is presented and discussed. Full article
Figures

Open AccessArticle Lempel–Ziv Data Compression on Parallel and Distributed Systems
Algorithms 2011, 4(3), 183-199; doi:10.3390/a4030183
Received: 29 July 2011 / Revised: 23 August 2011 / Accepted: 30 August 2011 / Published: 14 September 2011
Cited by 2 | PDF Full-text (167 KB) | HTML Full-text | XML Full-text
Abstract
We present a survey of results concerning Lempel–Ziv data compression on parallel and distributed systems, starting from the theoretical approach to parallel time complexity to conclude with the practical goal of designing distributed algorithms with low communication cost. Storer’s extension for image compression is also discussed.
[...] Read more.
We present a survey of results concerning Lempel–Ziv data compression on parallel and distributed systems, starting from the theoretical approach to parallel time complexity to conclude with the practical goal of designing distributed algorithms with low communication cost. Storer’s extension for image compression is also discussed. Full article
(This article belongs to the Special Issue Data Compression, Communication and Processing)
Open AccessArticle Approximating Frequent Items in Asynchronous Data Stream over a Sliding Window
Algorithms 2011, 4(3), 200-222; doi:10.3390/a4030200
Received: 23 June 2011 / Revised: 23 June 2011 / Accepted: 10 September 2011 / Published: 22 September 2011
Cited by 1 | PDF Full-text (405 KB) | HTML Full-text | XML Full-text
Abstract
In an asynchronous data stream, the data items may be out of order with respect to their original timestamps. This paper studies the space complexity required by a data structure to maintain such a data stream so that it can approximate the set
[...] Read more.
In an asynchronous data stream, the data items may be out of order with respect to their original timestamps. This paper studies the space complexity required by a data structure to maintain such a data stream so that it can approximate the set of frequent items over a sliding time window with sufficient accuracy. Prior to our work, the best solution is given by Cormode et al. [1], who gave an O (1/ε log W log (εB/ log W) min {log W, 1/εlog |U|)- space data structure that can approximate the frequent items within an ε error bound, where W and B are parameters of the sliding window, and U is the set of all possible item names. We gave a more space-efficient data structure that only requires O (1/ε log W log (εB/ logWlog log W) space. Full article

Journal Contact

MDPI AG
Algorithms Editorial Office
St. Alban-Anlage 66, 4052 Basel, Switzerland
algorithms@mdpi.com
Tel. +41 61 683 77 34
Fax: +41 61 302 89 18
Editorial Board
Contact Details Submit to Algorithms
Back to Top