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Posts Tagged ‘graduate-school’

With the news today about a proposed overhaul of college financial aid that would create a dependence between aid programs and the affordability of an institution, there is a sense that the trend of migrating more collegiate-level education to the online classroom will continue at an accelerated pace.

In order for an educational institution to improve affordability and value for students, they drastically need to either cut costs, improve enrollment using the same resources, or both. Online education has the potential to reach whole new markets around the world, as shown by the recent example of Sebastian Thrun‘s class Introduction to Artificial Intelligence. The Stanford professor allowed anyone to enroll for the class for free and taught the exact same course material and handed out the same homework assignments as the paying students. The response was overwhelming, to the tune of more than 160,000 students world-wide. Some students created an online study group on the aggregation website Reddit. Here is NPR’s story about Thrun’s class on All Things Considered.

That this is more affordable to an institution is unquestionable. Once the lectures are recorded, universities need only provide the server capacity to handle student clients from all over the world. Online tests and homework assignments make the job of grading that much easier. Humans need not be involved once everything is in place.

The benefits of online education are numerous, but two points stand out above the rest: the lowering of educational costs, and the ease with which quality education will reach parts of the world (and the country) where this was not possible before. One of the greatest causes for concern with a young family is the kids’ college fund. Wages have to keep up not only with inflation, but with already-astronomical and still rising educational costs.

Thrun’s experiment in reaching students around the world made him realize the importance of reaching such a wide and socio-economically disadvantaged audience. He has now started an online university called Udacity, offering free online coursework to anyone around the world. Other initiatives have been in place for longer, such as the Khan Academy, MIT’s OpenCourseWare initiative and the OpenCourseWare Consortium.

Initiatives like these indicate that the established providers of quality education are about to see a rapid rise in competition for students and their tuition fees. As the competition heats up, there is a push for more conventional universities to shift to a more technology-driven curriculum in order to lower their cost-per-student. It may be easy to dismiss faculty concerns as threats to entrenched interests, but there are some genuine concerns.

Once the material has been recorded and uploaded, universities have little incentive to update the material as often, given the relatively higher cost to re-record lectures and keep the material fresh. There would be a disturbance in the environment that fosters bidirectional exchanges of ideas and the organic atmosphere between students and instructors that tends to improve lecture styles year-over-year. The material and focus of the lectures may not be as dynamic and responsive to student needs as the semester progresses. Finally, there would be a threat to the teaching profession as fewer professors are hired, reducing the amount of fundamental research done at the university.

Indeed at Stanford University itself, there is a renewed sense of urgency to provide a more diverse portfolio of online coursework such as their Center for Professional Development and the Stanford Engineering Everywhere programs. It remains to be seen whether the online classroom will ultimately prove to be a great boon to education, but it is clear that the upside in the short-term far outweighs the downside.

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My PhD is officially complete. The final doctoral defense took place today and I can thankfully say that I passed with flying colors. The dissertation is titled Tunable Mismatch Shaping for Bandpass Delta-Sigma Data Converters. I’m looking forward to a long summer of rest, particularly after the intensity of the past several months.

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The final doctoral defense for my PhD has been scheduled for 1 PM on April 20, 2011, taking place in ACE 2.404B on-campus at the University of Texas. My dissertation is titled Tunable Mismatch Shaping for Bandpass Delta-Sigma Data Converters.

From the abstract:

Oversampled digital-to-analog converters typically employ an array of unit elements to drive out the analog signal. Manufacturing defects can create errors due to mismatch between the unit elements, leading to a sharp reduction in the effective dynamic range through the converter. Mismatch noise shaping is an established technique for alleviating these effects, but usually anchors the signal band to a fixed frequency location. In order to extend these advantages to tunable applications, this work explores a series of techniques that allow the suppression band of the mismatch noise shaping function to have an adjustable center frequency. The proposed techniques are implemented in hardware and evaluated according to mismatch shaping performance, latency and hardware complexity.

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Today, I presented a guest lecture to a class of graduate students at the University of Texas at Austin. The topic was Parallel Sorting Networks, and covered material from the seminal Introduction to Algorithms, by Cormen Leiserson and Rivest.

The problem statement: How can a random selection of N numbers be sorted in sub-linear time? Sorting is indeed a well-known problem, and there exist numerous algorithms and implementations in serially-computed software instructions. However, a sorting network is a comparison network in which multiple comparisons can be performed in parallel. The aim of the lecture was to provide a methodical construction of parallel sorting networks in hardware.

There are few assumptions on the input to such a network, consisting of N arbitrarily-ordered numbers which can be compared to one another. The expected output is a list of N numbers in a positionally-sorted order, where the sorting direction can be set to either ascending or descending order. N is assumed to be a power-of-2, but the techniques can be extended to non-power-of-2.

Besides the functional goal above, there is an efficiency goal to reduce the network complexity, i.e. number of comparisons, whilst maintaining a shallow network depth from input to output. In hardware terms, this translates to maintaining low hardware complexity whilst shortening the latency through the network. Low latency is particularly important for stability when such a system is used within an automatic feedback loop.

Chapter 28 in the aforementioned textbook on Algorithms covers this topic extremely well. The authors present a step-by-step approach to solving this problem and provide some good references. Parallel sorting is an old topic, and has been covered as far back as Donald Knuth‘s Sorting and Searching chapter in Volume 3 of The Art of Computer Programming from 1973, and further. There will likely never be an end to applications for these methods.

I concluded the talk with an application example that is very relevant to my current research. A fast and small parallel sorting network is needed within the vector quantizer of a vector-based mismatch shaper. In this case, the vector quantizer is used within the feedback loop of a Delta-Sigma data converter.

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This week, I presented a paper entitled Tunable Mismatch Shaping for Quadrature Bandpass Delta-Sigma Data Converters at the 2010 IEEE Workshop on Signal Processing Systems. This paper extends mismatch-shaping methods to quadrature data converters, and is co-authored with my doctoral advisor, Prof. Earl E. Swartzlander, Jr. The conference was held at the Cypress hotel in Cupertino, California. The presentation took place on Thursday, October 7, during Lecture Session 3: Application-Specific Signal Processing Architectures.

From the abstract:

Quadrature bandpass delta-sigma data converters are widely used in low-IF receiver applications where high linearity is required over a narrow bandwidth. A quadrature delta-sigma modulator with multibit quantization requires a digital-to-analog converter (DAC) for each of the in-phase (I) and quadrature (Q) paths. Device mismatch errors in the DAC can seriously degrade overall converter performance by adding I/Q path-mismatch and distortion. Mismatch noise shaping is an established technique for overcoming these limitations in a complex DAC, but usually anchors the signal band to a fixed frequency location. In order to apply mismatch shaping to applications that require tunable signal band locations, this paper presents a technique that allows the center frequency of the mismatch noise shaping transfer function through the complex DAC to be adjustable over the entire Nyquist range.

A pre-print version of the paper can be downloaded from here (pdf).

Edit-2011: The paper is now available on IEEExplore.

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Today was spent preparing and presenting my paper (co-authored with my doctoral adviser, Prof. Earl E. Swartzlander, Jr.) entitled A novel technique for Tunable Mismatch Shaping in Oversampled Digital-to-Analog Converters, during a poster session at the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). The poster session was titled DISPS-P1: Analog and Digital Signal Processing Systems, and provided an opportunity to spend time with researchers working on many other interesting topics. My poster was positioned right next to Professor Mark Arnold, who was presenting his poster on Implementing LNS using Filtering Units of GPUs, and I was quite fascinated to hear that GPUs were now being leveraged for real-time co-processing applications in order to eke out more processor performance.

Located in the heart of downtown Dallas, the Sheraton hotel is as unexciting a conference hotel as they come, with more than adequate facilities for big gatherings, but little else on offer. it didn’t help that the limited selection of restaurants and coffee shops in the vicinity left much to be desired. The conference itself was quite well-attended, and as is to be expected, with a very significant proportion of papers and posters having to do with speech and audio processing. The word of the day was most certainly Compressive Sensing (CS), an area of research pioneered at my alma mater, Rice University, and the talks featuring CS were by far the most heavily-attended.

I enjoyed the experience of presenting my research to others, particularly those whose work was so far removed from mine that I found myself resorting to first principles in order to convey the fundamental ideas. A pre-publication version of the paper can be downloaded here (pdf).

From the abstract:

Over-sampled digital-to-analog converters typically employ a unit-element architecture to drive out the analog signal. Performance can suffer from errors due to mismatch between unit elements, leading to a sharp drop in the achievable signal-to- noise ratio (SNR). Mismatch noise shaping is an established technique for overcoming these limitations, but usually anchors the signal band to a fixed location. In order to extend these advantages to tunable applications, this paper presents a novel technique that allows the mismatch noise shaping transfer function to have an adjustable center frequency.

Edit-2011: The paper is now available on IEEExplore.

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Last week, I presented my paper Tunable N-Path Mismatch Shaping for Multibit Bandpass Delta-Sigma Modulators at the 43rd Asilomar Conference on Signals, Systems and Computers.

From the abstract:

Many radio applications require the use of programmable bandpass Delta-Sigma converter. In the digital-to-analog converter (DAC) used within a Delta-Sigma converter, non-linearities created by DAC element mismatch error can be spectrally shaped to fall outside the signal band. The mismatch shapers within these converters thus also need to be programmable in order to follow the signal band. This paper proposes a new technique that tunes the center frequency of a mismatch noise transfer function while using an arbitrary mismatch shaping algorithm.

A pre-publication copy of the paper can be found here.

Edit-2010: the paper has finally been uploaded to IEEExplore.

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