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You are kindly invited to:
Sub-Nyquist Sampling (Xampling) - Smart Sampling
Wednesday, March 21, 2012, 8:30 - 14:25
Auditorium 280, 2nd floor, Electrical Engineering Building, Technion

Launching new area of activity in the EE Department, Technion

 

Sub-Nyquist Sampling (Xampling) - Smart Sampling

 

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The activity will be based on research performed by a team led 

 

by Prof. Yonina Eldar.
 

Activities include research and implementation of demo systems in cooperation with the High Speed Digital Systems Laboratory at the Department of Electrical Engineering.

 

Schedule

11:20 - 11:40

Compressed Beamforming in Ultrasound Imaging
Noam Wagner
EE Department, Technion


 

Noam Wagner

M.Sc. student,EE DepartmentTechnion

 

Abstract:

Emerging sonography techniques often require increasing the number of transducer elements involved in the imaging process. Consequently, larger amounts of data must be acquired and processed. The significant growth in the amounts of data affects both machinery size and power consumption. Within the classical sampling framework, state of the art systems reduce processing rates by exploiting the bandpass bandwidth of the detected signals. It has been recently shown, that a much more significant sample-rate reduction may be obtained, by treating ultrasound signals within the Finite Rate of Innovation framework. These ideas follow the spirit of Xampling, which combines classic methods from sampling theory with recent developments in Compressed Sensing. Applying such low-rate sampling schemes to individual transducer elements, which detect energy reflected from biological tissues, is limited by the noisy nature of the signals. This often results in erroneous parameter extraction, bringing forward the need to enhance the SNR of the low-rate samples. In our work, we achieve SNR enhancement, by beamforming the sub-Nyquist samples obtained from multiple elements. We refer to this process as ``compressed beamforming". Applying it to cardiac ultrasound data, we successfully image macroscopic perturbations, while achieving a nearly eight-fold reduction in sample-rate, compared to standard techniques.

 



?What is Sub-Nyquist Sampling  

We live in an analog world, but data processing is usually performed by digital computers.
The transition from the analog (continuous time) to the digital world is called sampling. 

In most analog-to-digital converters (ADCs) today, sampling is based on the Shannon-Nyquist theorem, which requires sampling at a rate that is at least twice the highest signal frequency.

As the bandwidth of the signal increases, it demands the increase in sampling frequency, which raises a number of critical issues that affect system design:

  • There is a need for expensive wideband ADCs which require excessive hardware solutions and consume a lot of power.
  • Computer systems need more memory and more computing power in order to process the sampled data. In many cases, much of the sampled information is compressed and reduced in later stages of the processing.

Sub-Nyquist sampling offers a new way of smart and effective sampling of wideband signals by performing analog preprocessing prior to sampling. The idea is to exploit the same structure that is used in the digital chain in order to drastically reduce the sampling rate and only sample the information in the signal that is actually needed. Thus, instead of sampling at a high rate and then compressing the data, it is possible to sample the signal at a low rate to begin with. Low sampling rate also enables low-rate digital processing and reduces required system memory and power.
 

This technology has many potential applications in a large variety of fields such as communications, radar systems, medical imaging, optical systems, super-resolution microscopy and more.

 

At the event we will present algorithms and systems developed in the area of sub-Nyquist sampling.

 

 

Recent review articles:

  1. M. Mishali and Y. C. Eldar, "Sub-Nyquist Sampling: Bridging Theory and Practice", IEEE Signal Processing Magazine, vol. 28, no. 6, pp. 98-124, Nov. 2011.
  2. Skipping over Nyquist  (in Hebrew)  - מדלגים על נייקוויסט
  3. M. Mishali and Y. C. Eldar, "Xampling: Compressed Sensing for Analog Signals", Compressed Sensing: Theory and Applications, Edited by Y. C. Eldar and G. Kutyniok, Cambridge University Press, 2012.

 

Additional information on Xampling can be found at Prof. Yonina Eldar’s website.

For further information on Xampling demo systems click here.

 

We look forward to seeing you at the event.

Please feel free to forward this invitation within your organization.

 

Best regards,

 

Yonina Eldar

 

 

For more information please contact Suzie Eid:

Email: suzie@ef.technion.ac.il, 972 4 829-5925. Ina Rivkin Email: inna@ee.technion.ac.il, 972 4 829-4789

 

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