Robert J Marks Ii William A Dembski Popular Books

Robert J Marks Ii William A Dembski Biography & Facts

Robert Jackson Marks II (born August 25, 1950) is an American electrical engineer, computer scientist and Distinguished Professor at Baylor University. His contributions include the Zhao-Atlas-Marks (ZAM) time-frequency distribution in the field of signal processing, the Cheung–Marks theorem in Shannon sampling theory and the Papoulis-Marks-Cheung (PMC) approach in multidimensional sampling. He was instrumental in the defining of the field of computational intelligence and co-edited the first book using computational intelligence in the title. A Christian and an old earth creationist, he is a subject of the 2008 pro-intelligent design motion picture, Expelled: No Intelligence Allowed. Professional career 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. 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. 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). He is a Fellow of the IEEE and the Optical Society of America. Technical contributions Marks is a researcher in the area of electrical engineering. Treatment of prostate cancer. Marks and his colleagues developed algorithms for real time identification of placement of radioactive seeds in cancerous prostates. For this work, he was a co-recipient of the Judith Stitt Best Abstract Award from the American Brachytherapy Society. The algorithm is used clinically. 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 noise "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." Power load forecasting using neural networks. With his colleagues at the University of Washington, Marks was the first to apply an artificial neural network to forecast power demands for utilities in 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. 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. 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. A generalization of the Smith Chart, the Smith Tube is currently in Keysight's Advanced Design System (ADS) software package. Convolutional neural networks. With Homma and Atlas, Marks developed a temporal convolutional neural network 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. The ZAMD is a special case of Cohen's class of time-frequency distributions. The ZAMD is currently in the MATLAB Time-Frequency Toolbox and National Instruments' LabVIEW Tools for Time-Frequency, Time-Series, and Wavelet Analysis The ZAMD has been applied in numerous areas: "[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." "The ZAM-TFD [ZAMD] has been shown to be effective in tracking frequency hopping signals and representing signals in the presence of white noise." "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." "[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." Remote sensing. Marks and his colleagues 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. Wireless arrays. Marks is a co-recipient of a NASA Tech Brief for pioneering power efficient communication in wireless arrays. 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. "[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." Marks has made contributions to the sampling theorem including authoring the first book exclusively dedicated to the subject. Restoration of lost samples. Using "sophisticated estimation of the missing samples using previous and future samples," Marks 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." Ill-posed sampling (The Cheung-Marks Theorem). The sampling theorem's Cheung–Marks theorem 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. 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 Cheung extended the generalized sampling expansion of Athanasios Papoulis to higher dimensions. "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 so.... Discover the Robert J Marks Ii William A Dembski popular books. Find the top 100 most popular Robert J Marks Ii William A Dembski books.