Robert J. Marks II

Marks has received his bachelor's and master's degrees from Rose–Hulman Institute of Technology in 1972 and 1973, respectively. During his doctoral studies at Texas Tech University, he was supervised by J.F. Walkup; his dissertation focused on optical signal processing.{{cite thesis |type=PhD |last=Marks II |first=Robert Jackson |date=1977 |title=Space-variant coherent optical processing |publisher=Texas Tech University}} He obtained his Ph.D. degree in 1977.

Marks is a Distinguished Professor of Electrical and Computer Engineering at Baylor University and serves as the Director of the Walter Bradley Center for Natural and Artificial Intelligence.[https://centerforintelligence.org/ Bradley Center home page] From 1977 to 2003, he was on the faculty of the University of Washington in Seattle. He was the first president of the Institute of Electrical and Electronics Engineers (IEEE) Neural Networks Council (now the IEEE Computational Intelligence Society).{{Cite web |title=IEEE Transactions on Neural Networks |url=https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=72 |access-date=2024-11-06 |website=IEEE Xplore}} He is a Fellow of the IEEE"For leadership and contributions to the field of neural networks."(1994)[https://www.ieee.org/membership/fellows/fellows-directory.html]{{cite web|last1=Robert J. Marks II|title=Curriculum Vitae|url=http://robertmarks.org/CV/CV.pdf|access-date=June 3, 2015}} and the Optical Society of America."For contributions to image recovery and synthesis, optical processing, and electro-optical neural networks." (1989)

Marks is a researcher in the area of electrical engineering.[http://marksmannet.com/RobertMarks/CV/CV.pdf] Marks's CV.

• Treatment of prostate cancer. Marks and his colleagues developed algorithms for real time identification of placement of radioactive seeds in cancerous prostates.[http://cialab.ee.washington.edu/REPRINTS/2002-07_FastCrossProjection.pdf] S. Narayanan, P.S. Cho and R.J. Marks II, "Fast Cross-Projection Algorithm for Reconstruction of Seeds in Prostate Brachytherapy", Med. Phys. 29 (7), July 2002, pp. 1572–1579.[http://home.comcast.net/~yamagoya/papers/FastCARS2.pdf] S. Narayanan, P.S. Cho and R.J. Marks II, "Three-dimensional seed reconstruction from an incomplete data set for prostate brachytherapy", Phys. Med. Biol., vol.49, pp. 3483–3494 (2004). For this work, he was a co-recipient of the Judith Stitt Best Abstract Award from the American Brachytherapy Society.[https://www.americanbrachytherapy.org/ American Brachytherapy Society homepage] The algorithm is used clinically.D.R. Reed, K.E. Wallner, S.Narayanan, S.G. Sutlief, E.C. Ford, P.S. Cho, "Intraoperative fluoroscopic dose assessment in prostate brachytherapy patients," International Journal of Radiation Oncology, Biology, Physics, Vol 63, Issue 1, September, 2005, pp. 301–307
• Optimal detection. In the field of detection theory, Marks and his colleagues developed the first closed form solution for the Neyman–Pearson optimal detection of signals in non-Gaussian noiseS. A. Kassam, Signal Detection in Non-Gaussian Noise. Springer Verlag, 1988.[http://marksmannet.com/RobertMarks/REPRINTS/1978_DetectionInLaplaceNoise.pdf Detection in Laplace noise] R.J. Marks II, G.L. Wise, D.G. Haldeman and J.L. Whited, IEEE Transactions on Aerospace and Electronic Systems, vol. AES-14, pp. 866–872 (1978).

{{quotation| "Marks, Wise, Haldeman and Whited have derived exact expressions for the test statistic distribution functions, and thus were able to analyze the performance of the optimal detector for given values of signal strength and sample size."M. W. Thompson, D. R. Halverson and G. L. Wise. "Robust Detection in Nominally Laplace Noise." IEEE Transactions on Communications, Volume 42 Issue 2-4, pp. 1651–1660, Feb–Apr. 1994}}

• Power load forecasting using neural networks. With his colleagues at the University of Washington, Marks was the firstA. Khotanzad, R. Afkhami-Rohani, Lu Tsun-Liang, A. Abaye, M. Davis, D.J. Maratukulam, "ANNSTLF-a neural-network-based electric load forecasting system," IEEE Transactions on Neural Networks, Volume 8, Issue 4, Jul 1997 pp. 835–846. to apply an artificial neural network to forecast power demands for utilities in 1991.D.C. Park, M.A. El-Sharkawi, R.J. Marks II, L.E. Atlas & M.J. Damborg, "Electric load forecasting using an artificial neural network", IEEE Transactions on Power Engineering, vol.6, pp. 442–449 (1991). Six years later neural networks were being used by 32 major North American utilities and remains in common use today. IEEE sponsors a MATLAB based webinar on use of neural networks in load forecasting.[https://spectrum.ieee.org/webinar/1705522] {{Webarchive|url=https://web.archive.org/web/20101016230716/https://spectrum.ieee.org/webinar/1705522|date=2010-10-16}} IEEE Spectrum Webinar, "Electricity Demand and Price Forecasting with MATLAB," A technique "similar to one already used to successfully forecast electrical load needs" has been used to forecast Dow Jones closing values using data from millions of Twitter messages.[http://newsinfo.iu.edu/news/page/normal/16074.html] "Analyzing almost 10 million tweets, research finds public mood can predict Dow days in advance," Indiana University Press Release.
• The Smith Tube. Marks was a member of the Baylor research team that introduced the Smith Tube, a visualization tool useful in advanced microwave systems design.Fellows, Matthew, Matthew Flachsbart, Jennifer Barlow, Charles Baylis, and Robert J. Marks. "The Smith Tube: Selection of radar chirp waveform bandwidth and power amplifier load impedance using multiple-bandwidth load-pull measurements." WAMICON 2014, pp. 1-5. IEEE, 2014.[https://robertmarks.org/REPRINTS/2014_The%20SmithTube.pdf] A generalization of the Smith Chart, the Smith Tube is currently in Keysight's Advanced Design System (ADS) software package.[https://www.linkedin.com/pulse/5-reasons-try-3d-smith-chart-broadband-pa-design-kaelly-farnham/ Agilent's "3D Smith Chart for Broadband PA Design" announcement]

• Convolutional neural networks. With Homma and Atlas, Marks developed a temporal convolutional neural network{{cite journal|last=Homma|first=Toshiteru|author2=Les Atlas |author3=Robert Marks II |title=An Artificial Neural Network for Spatio-Temporal Bipolar Patters: Application to Phoneme Classification|journal=Advances in Neural Information Processing Systems |volume=1|year=1988|pages=31–40|url=http://papers.nips.cc/paper/20-an-artificial-neural-network-for-spatio-temporal-bipolar-patterns-application-to-phoneme-classification.pdf}} used widely in Deep learning.
• Signal display in time and frequency. The Zhao-Atlas-Marks time-frequency distribution, (a.k.a. the ZAM distribution or ZAMD), was originally called the cone shaped time-frequency distribution.[http://marksmannet.com/RobertMarks/REPRINTS/1990-07_TheUseOfCone.pdf] Y. Zhao, L. E. Atlas, and R. J. Marks, "The use of cone-shape kernels for generalized time-frequency representations of nonstationary signals," IEEE Trans. Acoustics, Speech, Signal Processing, vol. 38, no. 7, pp. 1084–1091, July 1990
• The ZAMD is a special case of Cohen's class of time-frequency distributions.
• The ZAMD is currently in the MATLAB Time-Frequency Toolbox[http://tftb.nongnu.org/refguide.pdf] Time-Frequency Toolbox For Use with MATLAB and National Instruments' LabVIEW Tools for Time-Frequency, Time-Series, and Wavelet Analysis [http://www.ni.com/pdf/products/us/4msw69-70.pdf] National Instruments. LabVIEW Tools for Time-Frequency, Time-Series, and Wavelet Analysis. [http://zone.ni.com/reference/en-XX/help/372656A-01/lvtimefreqtk/tfa_cone_shaped_distribution/] TFA Cone-Shaped Distribution VI
• The ZAMD has been applied in numerous areas: {{quotation| "[The ZAMGTFR [ZAMD] has advantage over most of the other TFRs under conditions of low SNR and some characteristic features are easy to be extracted from the 2-D time-frequency plane."D. Zeng, X. Zeng, G. Lu, and B. Tang. "Automatic modulation classification of radar signals using the generalised time-frequency representation of Zhao, Atlas and Marks." IET radar, sonar & navigation 5, no. 4 (2011): 507–516. }}{{quotation| "The ZAM-TFD [ZAMD] has been shown to be effective in tracking frequency hopping signals and representing signals in the presence of white noise."James R. Bulgrin, Bernard J. Rubal, Theodore E. Posch, and Joe M. Moody. "Comparison of binomial, ZAM and minimum cross-entropy time-frequency distributions of intracardiac heart sounds." In Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on, vol. 1, pp. 383–387. IEEE, 1994. }}{{quotation| "The Zhao–Atlas–Marks distribution produces a good resolution in time and frequency domains. The ZAMD method reduces the interference resulting from the cross-terms present in multi-component signals. It is useful in resolving close spectral peaks and capturing non-stationary and multi-component signals."G.X. Chena and Z.R. Zhou, "Time–frequency analysis of friction-induced vibration under reciprocating sliding conditions," Wear, Volume 262, Issues 1–2, 4 January 2007, Pages 1–10 }}{{quotation| "[T]he Zhao-Atlas-Marks time-frequency distribution ... significantly enhances the time and frequency resolution and eliminates all undesirable cross terms. // The ZAM distribution has been applied to speech with remarkable results."Lokenath Debnath, Wavelet transforms and their applications, Birkhäuser Boston, (2001) p.355}}
• Remote sensing. Marks and his colleagues [http://marksmannet.com/RobertMarks/REPRINTS/1992-09_InversionOfSnowParameters.pdf] L. Tsang, Z. Chen, S. Oh, R.J. Marks II and A.T.C. Chang, "Inversion of snow parameters from passive microwave remote sensing measurements by a neural network trained with a multiple scattering model" IEEE Transactions on Goescience and Remote Sensing, vol. 30, no.5, pp. 1015–1024 (1992).A. Ishimaru, R.J. Marks II, L. Tsang, C.M. Lam, D.C. Park and S. Kitamaru, "Particle size distribution using optical sensing and neural networks", Optics Letters, vol.15, pp. 1221–1223 (1990). were the first to use neural network inversion in remote sensing. They measured snow parameters from microwave measurements made by satellites. Their general approach is widely used today.Vladimir M. Krasnopolsky and Helmut Schillerb, "Some neural network applications in environmental sciences. Part I: forward and inverse problems in geophysical remote measurements," Neural Networks, Volume 16, Issues 3–4, April–May 2003, pp. 321–334F. Van der Meer, "Geophysical inversion of imaging spectrometer data for geologic modelling," International Journal of Remote Sensing, Volume 21, Issue 2, pp. 387–393 (2000)
• Wireless arrays. Marks is a co-recipient of a NASA Tech Brief for pioneering power efficient communication in wireless arrays.[http://www.baylor.edu/pr/news.php?action=story&story=5781 NASA Recognizes Baylor Engineer For Innovative Technology ]A.K. Das, R.J. Marks II, M.A. El-Sharkawi, Payman Arabshahi and Andrew Gray, "Minimum Power Broadcast Trees for Wireless Networks: Optimization Using the Viability Lemma", Proceedings of the NASA Earth Science Technology Conference, June 11–13, 2002, Pasadena, CA
• Power generation. Working with Southern California Edison, Marks and his colleagues pioneered computational intelligence based methods for early detection of intermittent shorted windings in multi ton electric generators while the rotors were still turning.[http://cialab.ee.washington.edu/REPRINTS/1995-03_LocalizationOfWindingShorts.pdf] M.A. El-Sharkawi, R.J. Marks II, S.Oh, S.J. Huang, I. Kerszenbaum and A. Rodriguez, "Localization of Winding Shorts Using Fuzzified Neural Networks", IEEE Transactions on Energy Conversion, vol. 10, no.1, March 1995, pp. 147–155.)S. Guttormsson, R.J. Marks II, M.A. El-Sharkawi and I. Kerszenbaum, "Elliptical novelty grouping for on-line short-turn detection of excited running rotors", IEEE Transactions on Energy Conversion, IEEE Transactions on Volume: 14 1, March 1999, pp. 16–22{{quotation| "[Their diagnostic test performs] detection and localization of shorted turns in the DC field winding of turbine-generator rotors using novelty detection and fuzzified neural networks. Use of neural networks with fuzzy logic outputs and traveling wave techniques ... is an accurate locator of shorted turns in turbo-generator rotors."M.E. El-Hawary, Fuzzy System Theory in Electrical Power Engineering, (IEEE Press, 1998), p.xxiv}}
• Marks has made contributions to the sampling theorem including authoring the first book exclusively dedicated to the subject.R.J. Marks II, Introduction to Shannon Sampling and Interpolation Theory, Springer-Verlag, (1991).[http://marksmannet.com/RobertMarks/REPRINTS/1999_IntroductionToShannonSamplingAndInterpolationTheory.pdf]
• Restoration of lost samples. Using "sophisticated estimation of the missing samples using previous and future samples",Farokh A. Marvasti, Peter M. Clarkson, Miroslav V. Dokic, Ut Goenchanart, and Chuande Liu, "Reconstruction of Speech Signals with Lost Samples," IEEE Transactions on Signal Processing, Volume 40, Issue 12, pp. 2897–2903, December 1992. MarksR.J. Marks II, "Restoring lost samples from an oversampled bandlimited signal", IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-31, pp. 752–755 (1983). first showed that, when a signal is sampled above its Nyquist rate, lost samples "are redundant, in the sense that any finite number of them can be obtained from the remaining ones by solving a system of linear equations".P.J.S.G. Ferreira, Incomplete sampling series and the recovery of missing samples from oversampled bandlimited signals," IEEE Transactions on Signal Processing, (40) 1 pp. 225 227 (1992).
• Ill-posed sampling (The Cheung-Marks Theorem). The sampling theorem's Cheung–Marks theoremJohn L. Brown, Jr. and Sergio D. Cabrera, "On Well-Posedness of the Papoulis Generalized Sampling

Expansion," IEEE Transactions on Circuits and Systems, pp.554-556, 1991. shows that samples taken from a signal at or above the Nyquist rate may prove incapable of restoring the signal in the presence of small amounts of noise.[http://marksmannet.com/RobertMarks/REPRINTS/1985_IllPosedSamplingTheorems.pdf] K.F. Cheung and R.J. Marks II, "Ill-posed sampling theorems", IEEE Transactions on Circuits and Systems, vol. CAS-32, pp. 829–835 (1985).

• Optimal image sampling. An image is said to be optimally sampled when the samples per unit area are minimized subject to no degradation of the interpolated image. Marks's contributions to optimal image sampling include:
• The Papoulis-Marks-Cheung Approach. Marks and CheungR. J. Marks, II, "Multidimensional-signal sample dependency at Nyquist densities," J. Opt. Soc. Amer. A, vol. 3, pp. 268–273, Feb. 1986. K. F. Cheung and R. J. Marks, II, "Imaging sampling below the Nyquist density without aliasing," J. Opt. Soc. Amer. A, vol. 7, no. 1, pp. 92–105, Jan. 1990. K. F. Cheung, "A multidimensional extension of Papoulis' generalized sampling expansion with the application in minimum density sampling," in Advanced Topics in Shannon Sampling and Interpolation Theory, Robert J. Marks II, Editor. New York, NY, USA: Springer-Verlag, 1993, pp. 85–119. extended the generalized sampling expansion of Athanasios PapoulisAthanasios Papoulis, "Generalized sampling expansion," IEEE Trans. Circuits Syst., vol. 24, no. 11, pp. 652–654, Nov. 1977. to higher dimensions. {{quotation| "Marks and Cheung focused on images with a given spectral support region and an initial base sampling lattice such that the induced spectral replicas of this support region do not overlap. They then showed that cosets of some sublattice could be removed from the base lattice until the sampling density was minimal (in the Landau sense) or approached minimal ... [This] allows the sampling rate to be reduced until it equals or approaches the Landau minimum."}}
• Sub-Nyquist Sampling. Cheung and Marks [http://www.opticsinfobase.org/abstract.cfm?URI=josaa-7-1-92] K.F. Cheung and R.J. Marks II, "Image sampling below the Nyquist density without aliasing", Journal of the Optical Society of America A, vol.7, pp. 92–105 (1990) showed that images could be sampled below their Nyquist rate and still be recovered without aliasing. {{quotation| "[Their] very interesting multidimensional construction ... exploit[s] the [required] spectral gaps that occur when sampling multidimensional signals. Their approach is to slice the spectrum into narrow bands, and handle separately those bands which contain signal energy and those which do not."Cormac Herley and Ping Wah Wong, "Minimum Rate Sampling and Reconstruction of Signals with Arbitrary Frequency Support," IEEE Transactions on Information Theory, Vol 45, No. 5, July 1999, pp. 1555–1564. }}
• Optical computers. Marks invented [http://www.docstoc.com/docs/24151253/Coherent-optical-extrapolation-of-2-D-band-limited-signals] R.J. Marks II, "Coherent optical extrapolation of two-dimensional signals: processor theory", Applied Optics, vol. 19, pp. 1670–1672 (1980) and implemented R.J. Marks II and D.K. Smith "Gerchberg – type linear deconvolution and extrapolation algorithms", in Transformations in Optical Signal Processing, edited by W.T. Rhodes, J.R. Fienup and B.E.A. Saleh, SPIE vol. 373, pp. 161–178 (1984). an all optical computer that – using lenses, mirrors, and light from a laser – performs iterative calculations literally at the speed of light.{{quotation| "While many problems in optics can be solved by projections, it is difficult to solve such problems using all-optical methods. A notable exception is Marks' all-optical implementations of the convex projection algorithm for implementing super-resolution."Henry Stark and Yongyi Yang,Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics, Wiley-Interscience,(1998), p.281.}}

In 2006 Marks hired William Dembski as a part-time post-doctoral researcher; Dembski is an intelligent design proponent and former Baylor staff member at the heart of a previous intelligent design controversy at Baylor over the Michael Polanyi Center's promotion of intelligent design, which had been resolved when Baylor disbanded that center in 2000. Dembski's position in Marks' lab was funded by a $30,000 gift from the Lifeworks Foundation; the gift went through the university's development department and not its academic grant administration. Dembski's role was stated in the gift documents. Marks said that he kept Dembksi's presence quiet. By December 2006 Dembski's university position had been brought to the university administration's attention, and the university returned the unspent funds and terminated Dembski's position.{{cite news|last1=Briggs|first1=Brad|last2=Maalou|first2=Grace|title=BU had role in Dembski return|url=https://www.baylor.edu/content/services/document.php?id=55567|work=Baylor Lariat|date=November 27, 2007}}

Marks created a website to describe the work that he and Dembski were doing, which the website described as happening at the "Evolutionary Informatics Lab" at Baylor. In the summer of 2007 that website was called to the attention of the Baylor administration after Marks discussed that work on a podcast hosted by Casey Luskin of the Discovery Institute, and the university administration shut the website down. Marks challenged the removal.{{cite news|url=http://dailyorange.com/2007/09/baylor-forces-professor-to-shut-down-site/|title=Baylor forces professor to shut down site|work=The Daily Orange|first=Nicole |last=Loring|date=September 8, 2007 }}{{cite news|last1=Farrell|first1=Elizabeth F.|title=Baylor U. Removes a Web Page Associated With Intelligent Design From Its Site|url=https://www.chronicle.com/article/Baylor-U-Removes-a-Web-Page/121996|work=The Chronicle of Higher Education|date=4 September 2007}} {{subscription required}} The site was reposted to a server outside of Baylor.

The dispute over the website was covered in the 2008 pro-intelligent design film Expelled: No Intelligence Allowed.{{cite news|last1=Jablonski|first1=Stephen|title=Obviously not objective, 'Expelled' explores academic freedom|url=https://www.baylor.edu/lariatarchives/news.php?action=story&story=50601|work=The Baylor Lariat|date=April 22, 2008|language=en|access-date=May 17, 2018|archive-date=December 10, 2015|archive-url=https://web.archive.org/web/20151210161437/http://www.baylor.edu/lariatarchives/news.php?action=story&story=50601|url-status=dead}}

Marks served as the faculty adviser to the University of Washington's chapter of Campus Crusade for Christ for seventeen years. He has presented his talk "What Does Calculus Have to Do with Christianity?" [http://marksmannet.com/RobertMarks/Apologetics/Presentations/Christians_Calculus.ppt "What Does Calculus Have to Do with Christianity" Presentation] in Poland, Japan, Canada, Russia, and the United States.

Marks has made science-oriented Christian apologetics presentations.[http://marksmannet.com/RobertMarks/Apologetics/index_apologetics.htm Marks' apologetics page] Venues include Poland, Japan, Moscow, Canada, and Siberia.

• With William A. Dembski, Marks offered statistical arguments against James Cameron's claim to have found the burial site of Jesus as portrayed in Cameron's documentary The Lost Tomb of Jesus.[http://www.swbts.edu/campusnews/story.cfm?id=EE2ACCC1-15C5-E47C-F9151E4BE923EF11] Benjamin Hawkins, "Southwestern professors make no bones about Christ's resurrection," Mar 26, 2008[https://books.google.com/books?id=OGwrSciQGvsC&q=%22Buried+Hope+or+Risen+Savior%22+quarles] W.A. Dembski and R.J. Marks II, The Jesus Tomb Math," in Buried Hope Or Risen Savior?: The Search for the Jesus Tomb, edited by Charles Quarles.
• Marks has served as a consultant with Microsoft, DARPA, the Pacific Gas and Electric Company, The Boeing Company, the John Fluke Manufacturing Company, and Southern California Edison.
• Marks was the cartoonist[http://marksmannet.com/BobMarks/Cartoons/SketchMarks/index.htm] Sketch Marks (from Marks's web page.) for the student newspaper while at Rose–Hulman Institute of Technology.,{{Citation needed|date=May 2010}}
• Marks hosted a political radio talk show in the early 1970s.[http://marksmannet.com/BobMarks/MelodyMarks/MarksP3/w.htm] WPFR TeleTalk (from Marks's web page.)
• Marks's Erdős number is three and his Bacon number is two. Therefore, his Erdős–Bacon number is five.[http://marksmannet.com/BobMarks/FAQs/SupportFiles/Erdos.html] "Robert J. Marks II has an Erdős-Bacon number of five." Retrieved 2010-05-05.

• R.J. Marks II, Non-Computable You: What You Do Artificial Intelligence Never Will, Discovery Press, (2022). [https://noncomputableyou.com/]
• R.J. Marks II and William A. Dembski with J. P. Moreland, For a Greater Purpose: The Life and Legacy of Walter Bradley, Erasmus Press, (2020). [https://influencepublishers.com/product/for-a-greater-purpose/]
• R.J. Marks II, The Case for Killer Robots: Why America's Military Needs to Continue Development of Lethal AI, Discovery Institute Press, (2020). [https://discoveryinstitutepress.com/book/the-case-for-killer-robots/]
• R.J. Marks II, William A. Dembski and Winston Ewert, Introduction to Evolutionary Informatics, World Scientific, Singapore, (2017).[http://www.worldscientific.com/worldscibooks/10.1142/9974]
• R.J. Marks II, Michael Behe, William A. Dembski, Bruce L. Gordon, John C. Sanford, Editors, Biological Information - New Perspectives, World Scientific, Singapore, (2013).[http://www.worldscientific.com/worldscibooks/10.1142/8818#t=toc]
• R.J. Marks II, Handbook of Fourier Analysis and Its Applications, Oxford University Press, (2009).[http://www.handbookoffourieranalysis.com/]
• R. D. Reed and R.J. Marks II, Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks, MIT Press, Cambridge, MA, (1999).
• M. Palaniswami, Y. Attikiouzel, R.J. Marks II, David B. Fogel and Toshio Fukuda; Editors, Computational Intelligence: A Dynamic System Perspective, IEEE Press, (1995).
• R.J. Marks II, Editor, Fuzzy Logic Technology and Applications, IEEE Technical Activities Board, Piscataway, (1994).
• Jacek M. Zurada, R.J. Marks II and C.J. Robinson; Editors, Computational Intelligence: Imitating Life, (IEEE Press, 1994).
• R.J. Marks II, Editor, Advanced Topics in Shannon Sampling and Interpolation Theory, (Springer-Verlag, 1993).
• R.J. Marks II, Introduction to Shannon Sampling and Interpolation Theory, Springer-Verlag, (1991).[http://marksmannet.com/RobertMarks/REPRINTS/1999_IntroductionToShannonSamplingAndInterpolationTheory.pdf]
• M.A. El-Sharkawi and R. J. Marks II, Editors, Applications of Neural Networks to Power Systems, IEEE Press, Piscataway, (1991).

{{reflist}}

{{wikiquote}}

• [http://RobertMarks.org Robert J. Marks II, PhD] home page
• [http://www.ecs.baylor.edu/index.php?id=867230 Dr. Robert J. Marks II] Engineering Faculty, Baylor University

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