Ali Akansu

Ali Naci Akansu (born May 6, 1958) is a Turkish-American Professor of electrical & computer engineering and scientist in applied mathematics.

He is best known for his seminal contributions to the theory and applications of linear subspace methods including sub-band and wavelet transforms, particularly the binomial QMF[1][2] (also known as Daubechies wavelet) and the multivariate framework to design statistically optimized filter bank (eigen filter bank).[3][4]

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 (now New York 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.

In 1990, he showed that the binomial quadrature mirror filter bank (binomial QMF) is identical to the Daubechies wavelet filter, and interpreted and evaluated its performance from a discrete-time signal processing perspective. [5] It was an extension of his prior work on Binomial coefficient and Hermite polynomials that he developed the Modified Hermite Transformation (MHT) in 1987.[6][7] The magnitude square functions of Binomial-QMF filters are the unique maximally flat functions in a two-band PR-QMF design formulation.[8][9] He organized the first wavelet conference in the United States at NJIT in April 1990,[10] and, then in 1992[11] and 1994.[12] He published the first wavelet-related engineering book in the literature entitled Multiresolution Signal Decomposition: Transforms, Subbands and Wavelets in 1992.[13]

He made contributions in the areas of optimal filter banks,[14][15][16][17][18][19][20] nonlinear phase extensions of discrete Walsh-Hadamard transform[21] and discrete Fourier transform,[22] principal component analysis of first-order autoregressive process,[23] sparse approximation,[24] digital watermarking,[25] [26] [27] [28] [29] [30] financial signal processing and quantitative finance.[31][32][33] [34] His publications include the books A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading[35] and Financial Signal Processing and Machine Learning.[36]

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 Entertainment 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.[37]

According to the Mathematics Genealogy Project, as of October 2023, Akansu had a total of 25 doctorate students.[38]

Selected works
  • Akansu, Ali N.; Haddad, Richard A. (1992), Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets, Boston, MA: Academic Press, ISBN 978-0-12-047141-6
  • Akansu, Ali N.; Smith, Mark J. T. (1996), Subband and Wavelet Transforms: Design and Applications, Boston: Kluwer Academic Publishers, ISBN 978-0-7923-9645-1
  • Akansu, Ali N.; Medley, Michael J. (1999), Wavelet, Subband, and Block Transforms in Communications and Multimedia, Boston: Kluwer Academic Publishers, ISBN 978-0-7923-8507-3
  • Sencar, Husrev T.; Mahalingam Ramkumar; Akansu, Ali N. (2004), Data Hiding Fundamentals and Applications: Content Security in Digital Multimedia, Boston, MA: Academic Press, ISBN 978-0-12-047144-7
  • 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
  • Akansu, Ali N.; Kulkarni, Sanjeev R.; Malioutov, Dmitry M. (2016), Financial Signal Processing and Machine Learning, Hoboken, NJ: Wiley-IEEE Press, ISBN 978-1-118-74567-0

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. 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.
  4. H. Caglar, Y. Liu and A.N. Akansu, "Optimal PR-QMF Design for Subband Image Coding," Journal of Visual Communication and Image Representation, Vol.4, No. 3, pp. 242-253, Sept. 1993.
  5. A.N. Akansu, R.A. Haddad and H. Caglar, The Binomial QMF-Wavelet Transform for Multiresolution Signal Decomposition, IEEE Trans. Signal Process., pp. 13–19, January 1993.
  6. A.N. Akansu, Statistical Adaptive Transform Coding of Speech Signals. Ph.D. Thesis. Polytechnic University, 1987.
  7. R.A. Haddad and A.N. Akansu, A New Orthogonal Transform for Signal Coding, IEEE Transactions on Acoustics, Speech and Signal Processing, vol.36, no.9, pp. 1404-1411, September 1988.
  8. H. Caglar and A.N. Akansu, A Generalized Parametric PR-QMF Design Technique Based on Bernstein Polynomial Approximation, IEEE Trans. Signal Process., pp. 2314–2321, July 1993.
  9. O. Herrmann, On the Approximation Problem in Nonrecursive Digital Filter Design, IEEE Trans. Circuit Theory, vol CT-18, no. 3, pp. 411–413, May 1971.
  10. 1st NJIT Symposium on Wavelets, April 1990
  11. 2nd NJIT Symposium on Wavelets, March 1992
  12. 3rd NJIT Symposium on Wavelets, March 1994
  13. Akansu, Ali N.; Haddad, Richard A. (1992), Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets, Boston, MA: Academic Press, ISBN 978-0-12-047141-6
  14. A.N. Akansu and Y. Liu, "On Signal Decomposition Techniques," Optical Engineering, vol. 30, no. 7, pp. 912–920, July 1991.
  15. H. Caglar and A.N. Akansu, "A Generalized Parametric PR-QMF Design Technique Based on Bernstein Polynomial Approximation," IEEE Trans. Signal Process., vol. 41, no. 7, pp. 2314–2321, July 1993.
  16. R.A. Haddad and A.N. Akansu, "A Class of Fast Gaussian Binomial Filters for Speech and Image Processing," IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 39, pp. 723-727, March 1991.
  17. A.N. Akansu, "Filter Banks and Wavelets in Signal Processing: A Critical Review," Proc. SPIE Video Communications and PACS for Medical Applications (Invited Paper), pp. 330-341, vol. 1977, Berlin, Oct. 1993.
  18. M.V. Tazebay and A.N. Akansu, "Progressive Optimality in Hierarchical Filter Banks," Proc. of 1st International Conference on Image Processing (ICIP), pp. 825-829, vol. 1, Austin, Nov. 1994.
  19. A.N. Akansu, "Multiplierless 2-band perfect reconstruction quadrature mirror filter (PR-QMF) banks," US Patent (US5420891A), May 30, 1995.
  20. C.A. Gonzales and A.N. Akansu, "A Very Efficient Low-bit-rate Subband Image/Video Codec Using Shift-only PR-QMF and Zero-zone Linear Quantizers," Proc. IEEE ICASSP, vol. 4, pp. 2993-2996, April 1997.
  21. A.N. Akansu and R. Poluri, "Walsh-Like Nonlinear Phase Orthogonal Codes for Direct Sequence CDMA Communications," IEEE Trans. Signal Process., vol. 55, no. 7, pp. 3800–3806, July 2007.
  22. A.N. Akansu and H. Agirman-Tosun, "Generalized Discrete Fourier Transform: Theory and Design Methods," Proc. IEEE Sarnoff Symposium, pp. 1–7, March 2009
  23. M.U. Torun and A.N.Akansu, "An Efficient Method to Derive Explicit KLT Kernel for First-Order Autoregressive Discrete Process," IEEE Transactions on Signal Processing, vol. 61, no. 15, pp. 3944–3953, Aug. 2013.
  24. O. Yilmaz and A.N.Akansu, "Quantization of Eigen Subspace for Sparse Representation," IEEE Transactions on Signal Processing, vol. 63, no. 14, pp. 3616–3625, 15 July 2015.
  25. M. Ramkumar and A.N. Akansu, "A Robust Scheme for Oblivious Detection of Watermarks / Data Hiding in Still Images," Proc. SPIE Symposium on Voice, Video and Data Communication, vol. 3528, pp. 474-481, Boston, Nov. 1998.
  26. M. Ramkumar and A.N. Akansu, "Information Theoretic Bounds for Data Hiding in Compressed Images," Proc. IEEE 2nd Workshop on Multimedia Signal Processing, pp. 267-272, Redondo Beach, Dec. 1998.
  27. M. Ramkumar and A.N. Akansu, "On the Choice of Transforms for Data Hiding in Compressed Video," Proc. IEEE ICASSP, vol. VI, pp. 3049-3052, Phoenix, March 1999.
  28. M. Ramkumar and A.N. Akansu, "Self-Noise Suppression Schemes for Blind Image Steganography," Proc. SPIE Special Session on Image Security, vol. 3845, pp. 55-65, Boston, Sept. 1999.
  29. I.B. Ozer, M. Ramkumar and A.N. Akansu, "A New Methodology for Detection of Watermarks in Geometrically Distorted Images," Proc. IEEE ICASSP, vol. IV, pp. 1963-1966, Istanbul, June 2000.
  30. H.T. Sencar, M. Ramkumar and A.N. Akansu, "A Robust Type-III Data Hiding Technique Against Cropping and Resizing Attacks," Proc. IEEE ISCAS 2002, Scottsdale, AZ, May 2002.
  31. 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.
  32. 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.
  33. A.N. Akansu and A. Xiong, "Eigenportfolios of US Equities for the Exponential Correlation Model," Journal of Investment Strategies (Risk.net), pp. 55–77, Aug. 2020.
  34. A.N. Akansu, M. Avellaneda and A. Xiong, "Quant Investing in Cluster Portfolios," Journal of Investment Strategies (Risk.net), pp. 61–78, Dec. 2020.
  35. 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
  36. 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
  37. Fellow Class of 2008 Archived 13 April 2010 at the Wayback Machine IEEE: Fellow Class of 2008
  38. http://genealogy.math.ndsu.nodak.edu/id.php?id=74955 Mathematics Genealogy Project : Ali Naci Akansu
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