Ali Akansu

Ali N. Akansu is a Turkish American scientist best known for his contributions to the theory and applications of sub-band and wavelet transforms.

Biography

Akansu received his B.S. degree from the Istanbul Technical University, Turkey, in 1980, his M.S. and PhD degrees from the Polytechnic University, Brooklyn, New York, in 1983 and 1987, respectively, all in Electrical Engineering. Since 1987, he has been with the New Jersey Institute of Technology where he is a Professor of Electrical and Computer Engineering. He was a Visiting Professor at Courant Institute of Mathematical Sciences of the New York University, 2009-2010.

He showed that the binomial quadrature mirror filter bank (binomial QMF) is identical to the Daubechies wavelet filter, interpreted and evaluated its performance from a discrete-time signal processing perspective.[1][2][3] He organized the first wavelets conference in the United States at NJIT in April 1990,[4] and in 1992,[5] and co-authored the first wavelet-related engineering book published in the literature entitled Multiresolution Signal Decomposition: Transforms, Subbands and Wavelets.[6]

He made contributions in the areas of optimal filter banks,[7][8] nonlinear phase extensions of discrete Walsh-Hadamard transform [9] and discrete Fourier transform,[10] principal component analysis of first-order autoregressive process,[11] sparse approximation, [12] financial signal processing and quantitative finance.[13][14] He co-authored and co-edited the books in financial signal processing & engineering entitled A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading[15] and Financial Signal Processing and Machine Learning,[16] respectively.

He was a founding director of the New Jersey Center for Multimedia Research (NJCMR), 1996–2000, and NSF Industry-University Cooperative Research Center (IUCRC) for Digital Video, 1998–2000. He was the vice president for research and development of the IDT Corporation, 2000–2001, the founding president and CEO of PixWave, Inc. (an IDT subsidiary) that has built the technology for secure peer-to-peer video distribution over the Internet. He was an academic visitor at David Sarnoff Research Center (Sarnoff Corporation), at IBM's Thomas J. Watson Research Center, and at Marconi Electronic Systems.

He is an IEEE Fellow (since 2008) with the citation for contributions to optimal design of transforms and filter banks for communications and multimedia security.[17]

According to the Mathematics Genealogy Project, as of June 2016, Akansu had a total of 22 doctorate students.[18]

Selected works

References

  1. ↑ A.N. Akansu, An Efficient QMF-Wavelet Structure (Binomial-QMF Daubechies Wavelets), Proc. 1st NJIT Symposium on Wavelets, April 1990.
  2. ↑ A.N. Akansu, R.A. Haddad and H. Caglar, Perfect Reconstruction Binomial QMF-Wavelet Transform, Proc. SPIE Visual Communications and Image Processing, pp. 609–618, vol. 1360, Lausanne, Sept. 1990.
  3. ↑ A.N. Akansu, R.A. Haddad and H. Caglar, The Binomial QMF-Wavelet Transform for Multiresolution Signal Decomposition, IEEE Trans. Signal Processing, pp. 13–19, January 1993.
  4. ↑ 1st NJIT Symposium on Wavelets, April 1990
  5. ↑ 2nd NJIT Symposium on Wavelets, March 1992
  6. ↑ Akansu, Ali N.; Haddad, Richard A. (1992), Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets, Boston, MA: Academic Press, ISBN 978-0-12-047141-6
  7. ↑ H. Caglar, Y. Liu and A.N. Akansu, "Statistically Optimized PR-QMF Design," Proc. SPIE Visual Communications and Image Processing, pp. 86–94, vol. 1605, Boston, Nov. 1991.
  8. ↑ H. Caglar and A.N. Akansu, "A Generalized Parametric PR-QMF Design Technique Based on Bernstein Polynomial Approximation," IEEE Trans. Signal Processing, pp. 2314–2321, July 1993.
  9. ↑ A.N. Akansu and R. Poluri, "Walsh-Like Nonlinear Phase Orthogonal Codes for Direct Sequence CDMA Communications," IEEE Trans. Signal Processing, vol. 55, no. 7, pp. 3800–3806, July 2007.
  10. ↑ A.N. Akansu and H. Agirman-Tosun, "Generalized Discrete Fourier Transform: Theory and Design Methods," Proc. IEEE Sarnoff Symposium, pp. 1–7, March 2009
  11. ↑ M.U. Torun and A.N.Akansu, "An Efficient Method to Derive Explicit KLT Kernel for First-Order Autoregressive Discrete Process," IEEE Trans. on Signal Processing, vol. 61, no. 15, pp. 3944-3953, Aug. 2013.
  12. ↑ O. Yilmaz and A.N.Akansu, "Quantization of Eigen Subspace for Sparse Representation," IEEE Trans. on Signal Processing, vol. 63, no. 14, pp. 3616-3625, July 15 2015.
  13. ↑ A.N. Akansu and M.U. Torun, "Toeplitz Approximation to Empirical Correlation Matrix of Asset Returns: A Signal Processing Perspective," IEEE Journal of Selected Topics in Signal Processing, vol. 6, no. 4, pp. 319-326, Aug. 2012.
  14. ↑ M.U. Torun, A.N. Akansu and M. Avellaneda, "Portfolio Risk in Multiple Frequencies," IEEE Signal Processing Magazine, vol. 28, no. 5, pp. 61-71, Sept. 2011.
  15. ↑ Akansu, Ali N.; Torun, Mustafa U. (2015), A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading, Boston, MA: Academic Press, ISBN 978-0-12-801561-2
  16. ↑ Akansu, Ali N.; Kulkarni, Sanjeev R.; Malioutov, Dmitry M., Eds. (2016), Financial Signal Processing and Machine Learning, Hoboken, NJ: Wiley-IEEE Press, ISBN 978-1-118-74567-0
  17. ↑ http://www.ieee.org/membership_services/membership/fellows/chronology/fellows_2008.html IEEE: Fellow Class of 2008
  18. ↑ http://genealogy.math.ndsu.nodak.edu/id.php?id=74955 Mathematics Genealogy Project : Ali Naci Akansu

External links

This article is issued from Wikipedia - version of the 10/16/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.