Sorry, you need to enable JavaScript to visit this website.

Sampling and Reconstruction

A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals


Time-based sampling of continuous-time signals is an alternate sampling paradigm in which the signal is encoded using a sequence of non-uniform instants time. The standard methods for reconstructing bandlimited and shift-invariant signals from their time-encoded measurements employ alternating projections type methods. In this paper, we consider the problem of sampling and perfect reconstruction of periodic finite-rate-of-innovation (FRI) signals using crossing time-encoding machine (C-TEM) and integrate-and-fire TEM (IF-TEM).

Paper Details

Authors:
Submitted On:
14 May 2020 - 12:45pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

TEM FRI ICASSP20.pdf

(14)

Subscribe

[1] , "A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5316. Accessed: Jul. 04, 2020.
@article{5316-20,
url = {http://sigport.org/5316},
author = { },
publisher = {IEEE SigPort},
title = {A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals},
year = {2020} }
TY - EJOUR
T1 - A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5316
ER -
. (2020). A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals. IEEE SigPort. http://sigport.org/5316
, 2020. A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals. Available at: http://sigport.org/5316.
. (2020). "A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals." Web.
1. . A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5316

Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions


Although the Hilbert transform and the spectral factorization are of central importance in signal processing,

Paper Details

Authors:
Submitted On:
14 May 2020 - 12:03pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

BoPo_ICASSP2605.pdf

(13)

Subscribe

[1] , "Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5314. Accessed: Jul. 04, 2020.
@article{5314-20,
url = {http://sigport.org/5314},
author = { },
publisher = {IEEE SigPort},
title = {Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions},
year = {2020} }
TY - EJOUR
T1 - Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5314
ER -
. (2020). Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions. IEEE SigPort. http://sigport.org/5314
, 2020. Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions. Available at: http://sigport.org/5314.
. (2020). "Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions." Web.
1. . Computing Hilbert Transform and Spectral Factorization for Signal Spaces of Smooth Functions [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5314

Can every analog system be simulated on a digital computer?


A Turing machine is a model describing the fundamental limits of any realizable computer, digital signal processor (DSP), or field programmable gate array (FPGA). This paper shows that there exist very simple linear time-invariant (LTI) systems which can not be simulated on a Turing machine. In particular, this paper considers the linear system described by the voltage-current relation of an ideal capacitor. For this system, it is shown that there exist continuously differentiable and computable input signals such that the output signal is a continuous function which is not computable.

Paper Details

Authors:
Submitted On:
14 May 2020 - 6:54am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

BoPo_ICASSP2597.pdf

(16)

Subscribe

[1] , "Can every analog system be simulated on a digital computer?", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5281. Accessed: Jul. 04, 2020.
@article{5281-20,
url = {http://sigport.org/5281},
author = { },
publisher = {IEEE SigPort},
title = {Can every analog system be simulated on a digital computer?},
year = {2020} }
TY - EJOUR
T1 - Can every analog system be simulated on a digital computer?
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5281
ER -
. (2020). Can every analog system be simulated on a digital computer?. IEEE SigPort. http://sigport.org/5281
, 2020. Can every analog system be simulated on a digital computer?. Available at: http://sigport.org/5281.
. (2020). "Can every analog system be simulated on a digital computer?." Web.
1. . Can every analog system be simulated on a digital computer? [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5281

Computability of the Peak Value of Bandlimited Signals

Paper Details

Authors:
Holger Boche, Ullrich Mönich
Submitted On:
14 May 2020 - 3:33am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

icassp2020_computability_peak_presentation.pdf

(15)

Subscribe

[1] Holger Boche, Ullrich Mönich, "Computability of the Peak Value of Bandlimited Signals", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5251. Accessed: Jul. 04, 2020.
@article{5251-20,
url = {http://sigport.org/5251},
author = {Holger Boche; Ullrich Mönich },
publisher = {IEEE SigPort},
title = {Computability of the Peak Value of Bandlimited Signals},
year = {2020} }
TY - EJOUR
T1 - Computability of the Peak Value of Bandlimited Signals
AU - Holger Boche; Ullrich Mönich
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5251
ER -
Holger Boche, Ullrich Mönich. (2020). Computability of the Peak Value of Bandlimited Signals. IEEE SigPort. http://sigport.org/5251
Holger Boche, Ullrich Mönich, 2020. Computability of the Peak Value of Bandlimited Signals. Available at: http://sigport.org/5251.
Holger Boche, Ullrich Mönich. (2020). "Computability of the Peak Value of Bandlimited Signals." Web.
1. Holger Boche, Ullrich Mönich. Computability of the Peak Value of Bandlimited Signals [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5251

Effective Approximation of Bandlimited Signals and Their Samples

Paper Details

Authors:
Holger Boche, Ullrich Mönich
Submitted On:
14 May 2020 - 3:30am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

icassp2020_computability_grid_presentation.pdf

(16)

Subscribe

[1] Holger Boche, Ullrich Mönich, "Effective Approximation of Bandlimited Signals and Their Samples", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5250. Accessed: Jul. 04, 2020.
@article{5250-20,
url = {http://sigport.org/5250},
author = {Holger Boche; Ullrich Mönich },
publisher = {IEEE SigPort},
title = {Effective Approximation of Bandlimited Signals and Their Samples},
year = {2020} }
TY - EJOUR
T1 - Effective Approximation of Bandlimited Signals and Their Samples
AU - Holger Boche; Ullrich Mönich
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5250
ER -
Holger Boche, Ullrich Mönich. (2020). Effective Approximation of Bandlimited Signals and Their Samples. IEEE SigPort. http://sigport.org/5250
Holger Boche, Ullrich Mönich, 2020. Effective Approximation of Bandlimited Signals and Their Samples. Available at: http://sigport.org/5250.
Holger Boche, Ullrich Mönich. (2020). "Effective Approximation of Bandlimited Signals and Their Samples." Web.
1. Holger Boche, Ullrich Mönich. Effective Approximation of Bandlimited Signals and Their Samples [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5250

Track-before-detect for sub-Nyquist radar


Sub-Nyquist radars require fewer measurements, facilitating low-cost design, flexible resource allocation, etc. By applying compressed sensing (CS) method, such radars achieve close performance to traditional Nyquist radars. However in low signal-to-noise ratio (SNR) scenarios, detecting weak targets is challenging: low probability of detection and many spurious targets could occur in the recovery results of traditional CS method.

Paper Details

Authors:
Xiqin Wang
Submitted On:
13 May 2020 - 10:16pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Track_before_detect_for_sub_Nyquist_radar_presentation.pdf

(13)

Subscribe

[1] Xiqin Wang, "Track-before-detect for sub-Nyquist radar", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5194. Accessed: Jul. 04, 2020.
@article{5194-20,
url = {http://sigport.org/5194},
author = {Xiqin Wang },
publisher = {IEEE SigPort},
title = {Track-before-detect for sub-Nyquist radar},
year = {2020} }
TY - EJOUR
T1 - Track-before-detect for sub-Nyquist radar
AU - Xiqin Wang
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5194
ER -
Xiqin Wang. (2020). Track-before-detect for sub-Nyquist radar. IEEE SigPort. http://sigport.org/5194
Xiqin Wang, 2020. Track-before-detect for sub-Nyquist radar. Available at: http://sigport.org/5194.
Xiqin Wang. (2020). "Track-before-detect for sub-Nyquist radar." Web.
1. Xiqin Wang. Track-before-detect for sub-Nyquist radar [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5194

MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY


Multi-channel sparse blind deconvolution refers to the problem of learning an unknown filter by observing its circulant convolutions with multiple input signals that are sparse. It is challenging to learn the filter efficiently due to the bilinear structure of the observations with respect to the unknown filter and inputs, leading to global ambiguities of identification. We propose a novel approach based on nonconvex optimization over the sphere manifold by minimizing a smooth surrogate of the sparsity-promoting loss function.

Paper Details

Authors:
Laixi Shi, Yuejie Chi
Submitted On:
13 May 2020 - 5:30pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Slides for MSBD

(13)

Keywords

Additional Categories

Subscribe

[1] Laixi Shi, Yuejie Chi, "MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5153. Accessed: Jul. 04, 2020.
@article{5153-20,
url = {http://sigport.org/5153},
author = {Laixi Shi; Yuejie Chi },
publisher = {IEEE SigPort},
title = {MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY},
year = {2020} }
TY - EJOUR
T1 - MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY
AU - Laixi Shi; Yuejie Chi
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5153
ER -
Laixi Shi, Yuejie Chi. (2020). MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY. IEEE SigPort. http://sigport.org/5153
Laixi Shi, Yuejie Chi, 2020. MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY. Available at: http://sigport.org/5153.
Laixi Shi, Yuejie Chi. (2020). "MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY." Web.
1. Laixi Shi, Yuejie Chi. MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5153

Scalable trellis quantization for JPEG XS


Trellis quantization as structured vector quantizer is able to improve
the rate-distortion performance of traditional scalar quantizers. As such,
it has found its way into the JPEG~2000 standard, and also recently as an
option in HEVC. In this paper, a trellis quantization option for JPEG XS is
considered and analyzed; JPEG~XS is a low-complexity, low-latency high-speed
"mezzanine" codec for Video over IP transmission in professional
production environments and industrial applications where high compression

Paper Details

Authors:
Submitted On:
19 March 2020 - 12:35pm
Short Link:
Type:
Event:
Presenter's Name:
Session:
Document Year:
Cite

Document Files

JPEGXS-Trellis.pdf

(47)

Subscribe

[1] , "Scalable trellis quantization for JPEG XS", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5005. Accessed: Jul. 04, 2020.
@article{5005-20,
url = {http://sigport.org/5005},
author = { },
publisher = {IEEE SigPort},
title = {Scalable trellis quantization for JPEG XS},
year = {2020} }
TY - EJOUR
T1 - Scalable trellis quantization for JPEG XS
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5005
ER -
. (2020). Scalable trellis quantization for JPEG XS. IEEE SigPort. http://sigport.org/5005
, 2020. Scalable trellis quantization for JPEG XS. Available at: http://sigport.org/5005.
. (2020). "Scalable trellis quantization for JPEG XS." Web.
1. . Scalable trellis quantization for JPEG XS [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5005

GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS


Generative models have recently received considerable attention in the field of compressive sensing. If an image belongs to the range of a pretrained generative network, we can recover it from its compressive measurements by estimating the underlying compact latent code. In practice, all the pretrained generators have certain range beyond which they fail to generate reliably. Recent researches show that convolutional generative structures are biased to generate natural images.

Paper Details

Authors:
M. Salman Asif
Submitted On:
4 December 2019 - 7:13am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Poster_GENERATIVE MODELS_Hyder

(69)

Subscribe

[1] M. Salman Asif, "GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4966. Accessed: Jul. 04, 2020.
@article{4966-19,
url = {http://sigport.org/4966},
author = {M. Salman Asif },
publisher = {IEEE SigPort},
title = {GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS},
year = {2019} }
TY - EJOUR
T1 - GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS
AU - M. Salman Asif
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4966
ER -
M. Salman Asif. (2019). GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS. IEEE SigPort. http://sigport.org/4966
M. Salman Asif, 2019. GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS. Available at: http://sigport.org/4966.
M. Salman Asif. (2019). "GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS." Web.
1. M. Salman Asif. GENERATIVE MODELS FOR LOW-RANK VIDEO REPRESENTATION AND RECONSTRUCTION FROM COMPRESSIVE MEASUREMENTS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4966

Bayesian Design of Sampling Set for Bandlimited Graph Signals


The design of sampling set (DoS) for bandlimited graph signals (GS) has been extensively studied in recent years, but few of them

Paper Details

Authors:
Submitted On:
15 November 2019 - 8:03am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

poster_xx.pdf

(69)

Keywords

Additional Categories

Subscribe

[1] , "Bayesian Design of Sampling Set for Bandlimited Graph Signals", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4959. Accessed: Jul. 04, 2020.
@article{4959-19,
url = {http://sigport.org/4959},
author = { },
publisher = {IEEE SigPort},
title = {Bayesian Design of Sampling Set for Bandlimited Graph Signals},
year = {2019} }
TY - EJOUR
T1 - Bayesian Design of Sampling Set for Bandlimited Graph Signals
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4959
ER -
. (2019). Bayesian Design of Sampling Set for Bandlimited Graph Signals. IEEE SigPort. http://sigport.org/4959
, 2019. Bayesian Design of Sampling Set for Bandlimited Graph Signals. Available at: http://sigport.org/4959.
. (2019). "Bayesian Design of Sampling Set for Bandlimited Graph Signals." Web.
1. . Bayesian Design of Sampling Set for Bandlimited Graph Signals [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4959

Pages