ESA LearnEO! Resource Library: Background www.learn-eo.org/resources.php?rid=1 Title: Using Filters to Reduce Speckle Noise in SAR Data Source: LearnEO! Tutorial Author: Valborg Byfield Licence: Creative Commons Attri

Source URL: www.learn-eo.org

• Signal processing
• Electromagnetism
• Computer vision
• Digital photography
• Filter theory
• Speckle noise
• Speckle pattern
• Image noise
• Median filter
• Image processing
• Electronics
• Electronic engineering

Sensing-Throughput Tradeoff for Cognitive Radio Systems with Unknown Received Power Ankit Kaushik1 , Shree Krishna Sharma2 , Symeon Chatzinotas2 , Bj¨orn Ottersten2 , and Friedrich Jondral1 1

Source URL: www.cel.kit.edu

• Throughput
• Distortion
• Estimation theory
• Signal processing
• Statistical inference

1996 Paper 9 Question 11 Information Theory and Coding Consider a noiseless analog communication channel whose bandwidth is 10,000 Hz. A signal of duration 1 second is received over such a channel. We wish to represent

Source URL: www.cl.cam.ac.uk

MOMENTS ESTIMATORS FOR HYPERGEOMETRIC DISTRIBUTIONS Jaakko Astola1 and Karen Gasparian2 and Eduard Danielian3 1 Institute of Signal Processing, Tampere University of Technology, Tampere, Finland, 2

Source URL: ticsp.cs.tut.fi

A Linear Model for Transcription Factor Binding Affinity Prediction in Protein Binding Microarrays Matti Annala1*, Kirsti Laurila1, Harri La¨hdesma¨ki2,3, Matti Nykter1,3 1 Department of Signal Processing, Tampere Univ

Source URL: www.cs.tut.fi

Summer School on Graphs in Computer Graphics, Image and Signal Analysis Bornholm, Denmark, August 2011 Outline Lecture 1: Monday (10:15 – 11:00) Introduction to the basic concepts of game theory

Source URL: www2.imm.dtu.dk

ESTIMATION OF SIGNAL INFORMATION CONTENT FOR CLASSIFICATION John W. Fisher III1 1 Michael Siracusa1

Source URL: people.csail.mit.edu

SGNBachelor’s Laboratory Course in Signal Processing Statistical Pattern Classification Recognition of Handwritten Digits 1

Source URL: www.cs.tut.fi

Balance between Noise and Information Flow Maximizes Set Complexity of Network Dynamics Tuomo Ma¨ki-Marttunen1,2*, Juha Kesseli1, Matti Nykter1 1 Department of Signal Processing, Tampere University of Technology, Tamper

Source URL: www.cs.tut.fi

R Foundations and Trends
in Signal Processing Vol. 1, No–304 c 2008 M. Gales and S. Young

Source URL: mi.eng.cam.ac.uk