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Signal Processing Education

“UpatrasECE” SPCUP 2016 Project Report

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Authors:
Ioannis Krillis, Maria Papaioannou
Submitted On:
29 May 2016 - 6:20am
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Report_ID24479.pdf

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[1] Ioannis Krillis, Maria Papaioannou, "“UpatrasECE” SPCUP 2016 Project Report", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1110. Accessed: Jul. 27, 2017.
@article{1110-16,
url = {http://sigport.org/1110},
author = {Ioannis Krillis; Maria Papaioannou },
publisher = {IEEE SigPort},
title = {“UpatrasECE” SPCUP 2016 Project Report},
year = {2016} }
TY - EJOUR
T1 - “UpatrasECE” SPCUP 2016 Project Report
AU - Ioannis Krillis; Maria Papaioannou
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1110
ER -
Ioannis Krillis, Maria Papaioannou. (2016). “UpatrasECE” SPCUP 2016 Project Report. IEEE SigPort. http://sigport.org/1110
Ioannis Krillis, Maria Papaioannou, 2016. “UpatrasECE” SPCUP 2016 Project Report. Available at: http://sigport.org/1110.
Ioannis Krillis, Maria Papaioannou. (2016). "“UpatrasECE” SPCUP 2016 Project Report." Web.
1. Ioannis Krillis, Maria Papaioannou. “UpatrasECE” SPCUP 2016 Project Report [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1110

Information on the MAST ENF Power Signature Dataset


At the intersection of signal processing and information forensics, the Signal Processing Cup 2016 global competition has explored a time-varying location-dependent signature of power grids that can be intrinsically captured in media recordings. This signature is called the Electric Network Frequency (ENF) signals. Throughout the SP Cup 2016 competition, participants were provided with multiple training, practice, and testing datasets that consisted of recordings made in different grids and containing ENF traces.

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24 October 2016 - 4:19pm
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Information on the MAST ENF Power Signature Dataset.pdf

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[1] , "Information on the MAST ENF Power Signature Dataset", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1108. Accessed: Jul. 27, 2017.
@article{1108-16,
url = {http://sigport.org/1108},
author = { },
publisher = {IEEE SigPort},
title = {Information on the MAST ENF Power Signature Dataset},
year = {2016} }
TY - EJOUR
T1 - Information on the MAST ENF Power Signature Dataset
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1108
ER -
. (2016). Information on the MAST ENF Power Signature Dataset. IEEE SigPort. http://sigport.org/1108
, 2016. Information on the MAST ENF Power Signature Dataset. Available at: http://sigport.org/1108.
. (2016). "Information on the MAST ENF Power Signature Dataset." Web.
1. . Information on the MAST ENF Power Signature Dataset [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1108

Lecture Notes on Digital Signal Processing


Lecture notes on digital signal processing for undergraduate and first-year graduate students.

These teaching materials are based on lectures developed at Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR, China.

The corresponding MATLAB files can be downloaded at

http://www.ee.cityu.edu.hk/~hcso/MATLAB.zip (779 downloads)

DSP.pdf

PDF icon DSP.pdf (1708 downloads)

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23 February 2016 - 1:43pm
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DSP.pdf

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[1] , "Lecture Notes on Digital Signal Processing", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/199. Accessed: Jul. 27, 2017.
@article{199-15,
url = {http://sigport.org/199},
author = { },
publisher = {IEEE SigPort},
title = {Lecture Notes on Digital Signal Processing},
year = {2015} }
TY - EJOUR
T1 - Lecture Notes on Digital Signal Processing
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/199
ER -
. (2015). Lecture Notes on Digital Signal Processing. IEEE SigPort. http://sigport.org/199
, 2015. Lecture Notes on Digital Signal Processing. Available at: http://sigport.org/199.
. (2015). "Lecture Notes on Digital Signal Processing." Web.
1. . Lecture Notes on Digital Signal Processing [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/199

How to Derive Bias and Mean Square Error for an Estimator?


Analyzing the performance of estimators is a typical task in signal processing. Two fundamental performance measures in the aspect of accuracy are bias and mean square error (MSE). In this presentation, we revisit a simple technique to produce the bias and MSE of an estimator that minimizes or maximizes an unconstrained differentiable cost function over a continuous space of the parameter vector under the small error conditions. This presentation is a companion work of: H. C. So, Y. T. Chan, K. C. Ho and Y.

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23 February 2016 - 1:43pm
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compute_bias_mse.pdf

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[1] , "How to Derive Bias and Mean Square Error for an Estimator?", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/194. Accessed: Jul. 27, 2017.
@article{194-15,
url = {http://sigport.org/194},
author = { },
publisher = {IEEE SigPort},
title = {How to Derive Bias and Mean Square Error for an Estimator?},
year = {2015} }
TY - EJOUR
T1 - How to Derive Bias and Mean Square Error for an Estimator?
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/194
ER -
. (2015). How to Derive Bias and Mean Square Error for an Estimator?. IEEE SigPort. http://sigport.org/194
, 2015. How to Derive Bias and Mean Square Error for an Estimator?. Available at: http://sigport.org/194.
. (2015). "How to Derive Bias and Mean Square Error for an Estimator?." Web.
1. . How to Derive Bias and Mean Square Error for an Estimator? [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/194

IEEE Signal Processing Society - State of the Society 2015


IEEE Signal Processing Society - State of the Society, at ICASSP 2015.  To access all previous years' speech:  http://www.signalprocessingsociety.org/about-sps/state-of-the-society/ To access the "what's signal processing" video: https://youtu.be/EErkgr1MWw0

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Submitted On:
15 June 2016 - 3:36pm
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State-of-the-Society ICASSP 2015.pdf

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[1] , "IEEE Signal Processing Society - State of the Society 2015", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/188. Accessed: Jul. 27, 2017.
@article{188-15,
url = {http://sigport.org/188},
author = { },
publisher = {IEEE SigPort},
title = {IEEE Signal Processing Society - State of the Society 2015},
year = {2015} }
TY - EJOUR
T1 - IEEE Signal Processing Society - State of the Society 2015
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/188
ER -
. (2015). IEEE Signal Processing Society - State of the Society 2015. IEEE SigPort. http://sigport.org/188
, 2015. IEEE Signal Processing Society - State of the Society 2015. Available at: http://sigport.org/188.
. (2015). "IEEE Signal Processing Society - State of the Society 2015." Web.
1. . IEEE Signal Processing Society - State of the Society 2015 [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/188

DSP Review - Teaching Slides


Review of DSP as a prelude to a graduate-level Advanced DSP course.

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Submitted On:
8 March 2017 - 11:03am
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part0_v1wm1_handoutAll.pdf

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[1] , "DSP Review - Teaching Slides", IEEE SigPort, 2014. [Online]. Available: http://sigport.org/98. Accessed: Jul. 27, 2017.
@article{98-14,
url = {http://sigport.org/98},
author = { },
publisher = {IEEE SigPort},
title = {DSP Review - Teaching Slides},
year = {2014} }
TY - EJOUR
T1 - DSP Review - Teaching Slides
AU -
PY - 2014
PB - IEEE SigPort
UR - http://sigport.org/98
ER -
. (2014). DSP Review - Teaching Slides. IEEE SigPort. http://sigport.org/98
, 2014. DSP Review - Teaching Slides. Available at: http://sigport.org/98.
. (2014). "DSP Review - Teaching Slides." Web.
1. . DSP Review - Teaching Slides [Internet]. IEEE SigPort; 2014. Available from : http://sigport.org/98

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