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Multirate Signal Processing

DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION


Directional block transforms (DBTs), such as discrete Fourier transforms, are basically less efficient for sparse image representation
than directional overlapped transforms, such as curvelet and contourlet, but have advantages in practical computation, such as less computational cost, less amount of memory usage to be used, and parallel processing. In order to realize efficient DBTs, this paper proposes

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Authors:
Seisuke Kyochi, Taizo Suzuki, Yuichi Tanaka
Submitted On:
1 March 2017 - 3:39am
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ICASSP2017_poster.pdf

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[1] Seisuke Kyochi, Taizo Suzuki, Yuichi Tanaka, "DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1536. Accessed: Dec. 18, 2017.
@article{1536-17,
url = {http://sigport.org/1536},
author = {Seisuke Kyochi; Taizo Suzuki; Yuichi Tanaka },
publisher = {IEEE SigPort},
title = {DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION},
year = {2017} }
TY - EJOUR
T1 - DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION
AU - Seisuke Kyochi; Taizo Suzuki; Yuichi Tanaka
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1536
ER -
Seisuke Kyochi, Taizo Suzuki, Yuichi Tanaka. (2017). DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION. IEEE SigPort. http://sigport.org/1536
Seisuke Kyochi, Taizo Suzuki, Yuichi Tanaka, 2017. DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION. Available at: http://sigport.org/1536.
Seisuke Kyochi, Taizo Suzuki, Yuichi Tanaka. (2017). "DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION." Web.
1. Seisuke Kyochi, Taizo Suzuki, Yuichi Tanaka. DIRECTIONAL DISCRETE COSINE TRANSFORMS ARISING FROM DISCRETE COSINE AND SINE TRANSFORMS FOR DIRECTIONAL BLOCK-WISE IMAGE REPRESENTATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1536

Bipartite Graph Filter Banks: Polyphase Analysis and Generalization


The work by Narang and Ortega (2012, 2013) laid the foundations for the two-channel critically sampled perfect reconstruction
filter bank for signals defined on undirected graphs. The basic filter bank proposed is applicable only to bipartite graphs but using the notion of separable filtering, the basic filter bank can be applied to any arbitrary undirected graphs. In this work several new theoretical results are presented.
In particular, the proposed polyphase analysis yields filtering

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Authors:
Antonio Ortega
Submitted On:
22 November 2016 - 7:04pm
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TSP_GFB_polyphase_sigport.pdf

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[1] Antonio Ortega, "Bipartite Graph Filter Banks: Polyphase Analysis and Generalization", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1296. Accessed: Dec. 18, 2017.
@article{1296-16,
url = {http://sigport.org/1296},
author = {Antonio Ortega },
publisher = {IEEE SigPort},
title = {Bipartite Graph Filter Banks: Polyphase Analysis and Generalization},
year = {2016} }
TY - EJOUR
T1 - Bipartite Graph Filter Banks: Polyphase Analysis and Generalization
AU - Antonio Ortega
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1296
ER -
Antonio Ortega. (2016). Bipartite Graph Filter Banks: Polyphase Analysis and Generalization. IEEE SigPort. http://sigport.org/1296
Antonio Ortega, 2016. Bipartite Graph Filter Banks: Polyphase Analysis and Generalization. Available at: http://sigport.org/1296.
Antonio Ortega. (2016). "Bipartite Graph Filter Banks: Polyphase Analysis and Generalization." Web.
1. Antonio Ortega. Bipartite Graph Filter Banks: Polyphase Analysis and Generalization [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1296

Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction


Signal processing on graphs finds applications in many areas. Motivated by recent developments, this paper studies the concept of spectrum folding (aliasing) for graph signals under the downsample-then-upsample operation. In this development, we use a special eigenvector structure that is unique to the adjacency matrix of M-block cyclic matrices. We then introduce M-channel maximally decimated filter banks. Manipulating the characteristics of the aliasing effect, we construct polynomial filter banks with perfect reconstruction property.

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Authors:
Oguzhan Teke, Palghat P. Vaidyanathan
Submitted On:
31 March 2016 - 6:00pm
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mchannel_graph_icassp_presentation_noTime.pdf

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[1] Oguzhan Teke, Palghat P. Vaidyanathan, "Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1077. Accessed: Dec. 18, 2017.
@article{1077-16,
url = {http://sigport.org/1077},
author = {Oguzhan Teke; Palghat P. Vaidyanathan },
publisher = {IEEE SigPort},
title = {Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction},
year = {2016} }
TY - EJOUR
T1 - Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction
AU - Oguzhan Teke; Palghat P. Vaidyanathan
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1077
ER -
Oguzhan Teke, Palghat P. Vaidyanathan. (2016). Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction. IEEE SigPort. http://sigport.org/1077
Oguzhan Teke, Palghat P. Vaidyanathan, 2016. Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction. Available at: http://sigport.org/1077.
Oguzhan Teke, Palghat P. Vaidyanathan. (2016). "Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction." Web.
1. Oguzhan Teke, Palghat P. Vaidyanathan. Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1077

Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction


Signal processing on graphs finds applications in many areas. Motivated by recent developments, this paper studies the concept of spectrum folding (aliasing) for graph signals under the downsample-then-upsample operation. In this development, we use a special eigenvector structure that is unique to the adjacency matrix of M-block cyclic matrices. We then introduce M-channel maximally decimated filter banks. Manipulating the characteristics of the aliasing effect, we construct polynomial filter banks with perfect reconstruction property.

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Authors:
Oguzhan Teke, Palghat P. Vaidyanathan
Submitted On:
31 March 2016 - 6:00pm
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mchannel_graph_icassp_presentation_noTime.pdf

(249 downloads)

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[1] Oguzhan Teke, Palghat P. Vaidyanathan, "Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1068. Accessed: Dec. 18, 2017.
@article{1068-16,
url = {http://sigport.org/1068},
author = {Oguzhan Teke; Palghat P. Vaidyanathan },
publisher = {IEEE SigPort},
title = {Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction},
year = {2016} }
TY - EJOUR
T1 - Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction
AU - Oguzhan Teke; Palghat P. Vaidyanathan
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1068
ER -
Oguzhan Teke, Palghat P. Vaidyanathan. (2016). Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction. IEEE SigPort. http://sigport.org/1068
Oguzhan Teke, Palghat P. Vaidyanathan, 2016. Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction. Available at: http://sigport.org/1068.
Oguzhan Teke, Palghat P. Vaidyanathan. (2016). "Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction." Web.
1. Oguzhan Teke, Palghat P. Vaidyanathan. Graph Filter Banks With M-Channels, Maximal Decimation, and Perfect Reconstruction [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1068

Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed

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Authors:
François Auger, Patrick Flandrin
Submitted On:
21 March 2016 - 5:51am
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poster_ICASSP16_21_01_2016.pdf

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[1] François Auger, Patrick Flandrin, "Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/919. Accessed: Dec. 18, 2017.
@article{919-16,
url = {http://sigport.org/919},
author = {François Auger; Patrick Flandrin },
publisher = {IEEE SigPort},
title = {Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed},
year = {2016} }
TY - EJOUR
T1 - Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed
AU - François Auger; Patrick Flandrin
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/919
ER -
François Auger, Patrick Flandrin. (2016). Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed. IEEE SigPort. http://sigport.org/919
François Auger, Patrick Flandrin, 2016. Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed. Available at: http://sigport.org/919.
François Auger, Patrick Flandrin. (2016). "Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed." Web.
1. François Auger, Patrick Flandrin. Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/919

Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing


4 TI_ADC

Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing

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Authors:
Simran Singh, Michael Epp, Wolfgang Schlecker and Mikko Valkama
Submitted On:
23 February 2016 - 1:44pm
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2015_Dec_GlobalSIP_4_TI-ADCs_Upload.ppt

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[1] Simran Singh, Michael Epp, Wolfgang Schlecker and Mikko Valkama, "Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/433. Accessed: Dec. 18, 2017.
@article{433-15,
url = {http://sigport.org/433},
author = {Simran Singh; Michael Epp; Wolfgang Schlecker and Mikko Valkama },
publisher = {IEEE SigPort},
title = {Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing},
year = {2015} }
TY - EJOUR
T1 - Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing
AU - Simran Singh; Michael Epp; Wolfgang Schlecker and Mikko Valkama
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/433
ER -
Simran Singh, Michael Epp, Wolfgang Schlecker and Mikko Valkama. (2015). Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing. IEEE SigPort. http://sigport.org/433
Simran Singh, Michael Epp, Wolfgang Schlecker and Mikko Valkama, 2015. Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing. Available at: http://sigport.org/433.
Simran Singh, Michael Epp, Wolfgang Schlecker and Mikko Valkama. (2015). "Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing." Web.
1. Simran Singh, Michael Epp, Wolfgang Schlecker and Mikko Valkama. Low-Complexity Digital Correction of 4-Channel Time-Interleaved ADC Frequency Response Mismatch using Adaptive I/Q Signal Processing [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/433