Wilamowski, Bogdan Maciej - Department of Electrical and Computer Engineering, Auburn University

• Implementing a Fuzzy System on a Field Programmable Michael McKenna and Bogdan M. Wilamowski
• IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 58, NO. 3, MARCH 2011 733 Compensation of Nonlinearities Using
• Sliding Mode Control of Nonlinear Systems Using Gaussian Radial Basis Function Neural Networks
• SPICE as a Fast and Stable Tool for Simulating a Wide Range of Dynamic Systems*
• 930 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 21, NO. 6, JUNE 2010 Improved Computation for LevenbergMarquardt
• Nicholas J. Cotton and Bogdan M. Wilamowski Electrical and Computer Engineering Auburn University
• Abstract With the dramatic increase of network bandwidth and decrease of network latency and because of
• How Not to Be Frustrated with Neural Networks BOGDAN M. WILAMOWSKI
• Figure 2. An example implementation of the third-order lowpass Butterworth ladder filter.
• 978-1-4244-3960-7/09/ $25.00 2009 IEEE 109 HSI 2009 Catania, Italy, May 21-23, 2009
• IEEE Article Data Extraction from Internet. , Bogdan M. Wilamowski**
• 3784 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 55, NO. 10, OCTOBER 2008 Computing Gradient Vector and Jacobian Matrix in
• Major Challenges of IEEE Transactions on Industrial Electronics by Bogdan M. (Dan) Wilamowski
• IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 54, NO. 1, FEBRUARY 2007 5 Message From the Incoming Editor-in-Chief
• Wide Band Tunable Filter Design Implemented in W. Matthew Anderson and Bogdan M. Wilamowski
• Computational Intelligence for Nonlinear Systems Bogdan M. Wilamowski
• IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 1, NO. 1, FEBRUARY 2005 1 Welcome to the IEEE TRANSACTIONS ON
• Method to Improve Total Dose Radiation Hardness in a CMOS dc-dc Boost
• 2005 3rd IEEE International Conference on Industrial Informatics (INDIN) Network traffic model for industrial environment
• 1. INTRODUCTION It is relatively easy to control linear systems.
• Silicon Implementation of Computational Intelligence for Mechatronics
• Welcome Message On behalf of the IEEE Industrial Electronics Society and on behalf of the organizing committee
• INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING Int. J. Adapt. Control Signal Process. 2003; 17: 489500 (DOI: 10.1002/acs.755)
• Gate-Controlled Punch Through Transistor Xiangli Li, Huadian Pan, Bogdan M. Wilamowski
• Abstract--High voltage (>15V) drivers are integrated into the VLSI chip for MEMS application with the development of SOC
• Random Weights Search in CompressedNeural Networks Using OverdeterminedPseudoinverse
• Robust Neural NetworkTrainingUsing Partial GradientProbing Milos Manic
• Radial Basis Function Neural Networks in Variable Structure Control of a Class of Biochemical Processes
• Paper Collection and Evaluation Through the Internet Aleksander Malinowski
• Towards the Attack Signatures' Comparison in Survivable Computer Networks Milos Manic Bogdan Wilamowski
• Fuzzy Preference Approach for Computer Network Attack Milos Manic, Bogdan Wilamowski
• Laboratory for the Introductory Digital Course Otto Fucik, Penn State University at Erie
• Soft Computing and its Application B. M. `Dan' Wilamowski
• VLSI Analog Signal B. M. `Dan' Wilamowski
• International Conference on Information Technology Based UNESCO Chair on Mechatronics Higher Education and Training, Istanbul, Turkey, July 3-5, 2000 Bogazici University, Istanbul, Turkey
• Establishment of a Sliding Mode in a Nonlinear System by Tuning the Parameters of a Fuzzy Controller
• Abstract -C networks, fuzzy
• 478 IEEE TRANSACTIONS ON EDUCATION, VOL. 39, NO. 4, NOVEMBER 1996 LAD ocomputer Tool for
• STATIC VAR COMPENSATOR CONTROL USING A QUANTIZED CONTROLLER FOR A TWO AREA MULTI-MACHINE SYSTEM
• CMOS Implementationof a Pulse-CoupledNeuron Cell Bogdan M. Wilamowski, Richard C. Jaeger, Mary Lou Padgett
• CMOS IMPLEMENTATION OF A PULSE-CODED NEURAL NETWORK WITH A CURRENT CONTROLLED OSCILLATOR
• 214 IEEETRANSACTIONSON EDUCATION, VOL. 38, NO. 3, AUGUST 1995 Methods of Removing Single Variable
• QUANTIZED CONTROLLER WITH CLOSE TO OPTIMUM NONLINEAR CONTROL Wing-Choi Ma and Bogdan M. Wilamowski
• Abstract -This paper introduces a neural network training tool through computer networks. The following algorithms,
• Advanced Controllers for Microelectromechanical Robert N. Dean, Jr. John Y. Hung Bogdan M. Wilamowski
• Session 2532 Web-based C++ Compiler
• Chemically vapor deposited diamond-tipped one-dimensional nanostructures and nanodiamondsilicananotube composites
• Neural Network Trainer with Second Order Learning Algorithms
• A VLSI Implementation of Mixed-Signal mode Bipolar Neuron Circuitry Dong Pan, and Bogdan. M. Wilamowski
• Advanced Learning Algorithms Bogdan M. Wilamowski
• High Speed, High Voltage, and Energy Efficient Static Induction Bogdan M. Wilamowski
• Microprocessor Implementation of Fuzzy Systems and Neural Jeremy Binfet
• A MODIFIED REGRESSION ALGORITHM FOR FAST ONE LAYER NEURAL NETWORK TRAINING
• Refining the Intelligence with a Task Specific Error Measure Mehmet nder Efe1
• Method of computing gradient vector and Jacobean matrix in arbitrarily connected neural networks
• Spatial to Temporal Conversion of Images Using A Pulse-Coupled Neural Network
• IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 10, NO. 3, MAY 1999 539 Analog Implementation of Pulse-Coupled
• SPICE based Circuit Analysis using Web Pages Bogdan Wilamowski, Aleksander Malinowski, John Regnier
• Abstract--The paper describes a neural network implementation on a low end and inexpensive microcontroller.
• Threshold Voltage Control for Deep Sub-micrometer Fully Depleted SOI MOSFET
• JOURNAL OF COMPUTING, VOLUME 3, ISSUE 3, MARCH 2011, ISSN 2151-9617 HTTPS://SITES.GOOGLE.COM/SITE/JOURNALOFCOMPUTING/
• VLSI implementation of cross-coupled MOS resistor circuits Phuoc T. Tran Bogdan M. Wilamowski
• Special Neural Network Architectures for Easy Electronic Implementations
• IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 21, NO. 11, NOVEMBER 2010 1793 Neural Network Learning without
• Active and Passive Filter Synthesis using BOGDAN M. WILAMOWSKI and RAMRAJ GOTTIPARTHY
• Abstract. In this paper, a neural architecture which gives identical TSK fuzzy system is proposed based on the area
• A Tunable CMOS Resistor with Wide Tuning Range for Low Pass Filter Application
• Abstract --Phase-Locked Loops (PLLs) are often used as frequency multiplier for generating high frequency clock
• Enhancing The Sensitivity of Miniaturized Quadrupole Mass Spectrometers Bodgan Wilamowski1
• High Speed, High Voltage, and Energy Efficient Static Induction Devices
• Human factor and computational intelligence limitations in resilient control systems
• Session 11b6 0-7803-5643-8/99/$10.00 1999 IEEE November 10 -13, 1999 San Juan, Puerto Rico
• 9th NASA Symposium on VLSI Design 2000 7.6.1 Low Power Current Mode Loser-Take-All
• Challenges in Applications of Computational Intelligence in Industrial Electronics
• Abstract--Electroencephalogram signals (EEG), also known as brainwaves, provide rich information about the brain processes,
• Simple way of teaching transistor amplifiers Bogdan M. Wilamowski
• Inkjet printing of nanodiamond suspensions in ethylene glycol for CVD growth of patterned diamond structures and practical applications
• 1266 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 48, NO. 6, DECEMBER 2001 Letters to the Editor________________________________________________________________
• A Relaxation/Regression Algorithm for Efficient Training of Multilayer Neural Networks
• 1100 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 47, NO. 5, OCTOBER 2000 Oil Well Diagnosis by Sensing Terminal
• IMPLEMENTATION OF RBF TYPE NETWORKS BY SIGMOIDAL FEEDFORWARD NEURAL NETWORKS
• Design and Optimization of PWL Circuits Used in Fuzzy Logic Hardware
• Efficient Algorithm for Training Neural Networks with one Hidden Layer Bogdan M. Wilamowski, Yixin Chen,
• Using Neural Networks to Predict Abnormal Returns of Quarterly Earnings
• Internet Technology as a Tool for Solving Engineering Problems Aleksander Malinowski
• A Gray-Code Current Mode ADC Structure Bogdan M. Wilamowski
• XV Krajowa Konferencja Automatyki, Warszawa 27-30 czerwca 2005 IMPLEMENTATION OF METHODS
• An Algorithm for Fast Convergence in Training Neural Bogdan M. Wilamowski
• Pulse-Coupled Neurons for Image Filtering Bogdan M. Wilamowski, Mary Lou Padgett1
• Current-Mode CMOS Implementation of a Fuzzy Min-Max Network Yasuhiro Ota and Bogdan M. Wilamowski
• Digitally Tuned Analog VLSI Controllers Bodgan M. Wilamowski*, John Y. Hung*, and Ramraj Gottiparthy*
• Mathematical and Computer Modelling of Dynamical Systems 1387-3954/02/0802-185$16.00 2002, Vol. 8, No. 2, pp. 185198 # Swets & Zeitlinger
• Creating a Sliding Mode in a Motion Control System by Adopting a Dynamic Defuzzification Strategy in an Adaptive Neuro Fuzzy
• Automated Data Mining from Web Servers Using Perl Script
• Abstract. In this paper, second order algorithms, such as Levenberg Marquardt algorithm [1][2], are recommended
• Chapter 1 -Introduction to SPICE 1 1.1. Fast Start 2
• 2004 IEEE InternationalConference an Industrial Technology (ICIT) Methods of Computational Intelligence
• NOVEL INDUCTORLESS NEURISTOR LINE Indexing terms: Delays, Neural nets
• IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 2, NO. 4, NOVEMBER 2006 213 Network Traffic Model for Industrial Environment
• Abstract--The paper describes a multiobjective optimization method which combines a second order algorithm with an
• Merge of Evolutionary Computation with Gradient Based Method for Optimization Problems
• IEEE TRANSACTIONS ON EDUCATION, VOL. 35,NO. 4, NOVEMBER 1992 35 I Personal Computer Support for Teaching
• A Synchronous High-Speed, High-Accuracy, Loser-Take-All Circuit Bogdan M. Wilamowski and Don L. Jordan,
• 1132 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 46, NO. 6, DECEMBER 1999 Neuro-Fuzzy Architecture for CMOS Implementation
• 2005 3rd IEEE International Conference on Industrial Informatics (INDIN) Improvement ofthe Computer Network Transmission Band Usage
• 144 IEEE TRANSACrIONS ON EDUCATION, VOL. 35, NO. 2, MAY 1992 An Electrical Network Approach to the
• 3374 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 55, NO. 9, SEPTEMBER 2008 Optimization Using a Modified Second-Order
• Neural Networks and Fuzzy Systems for Nonlinear Applications
• CMOS Architecture of Synchronous Pulse-Coupled Neural Network and Its Application to Image Processing
• Abstract--The paper presents a review of electronic noses with emphasis of the usage of live olfactory receptor neurons as
• Fabrication and Control of an Electrostatically Levitated Rotating Charles D. Ellis, Bogdan M. Wilamowski,
• Session 2793 GradeWatch the Software Package
• 12.1 Introduction The LevenbergMarquardt algorithm [L44,M63], which was independently developed by Kenneth
• Comparison between Traditional Neural Networks and Radial Basis Function Networks
• 59.1 Introduction User datagram protocol (UDP) is a part of TCP/IP suite [STD6,C02-1,F10,GW03,PD07]. It provides
• 11.1 Introduction The concept of systems that can be learned was well described over half a century ago by Nilsson [N65]
• 5.1 Introduction The fascination of artificial neural networks started in the middle of the previous century. First artificial
• How to not get frustrated with neural networks Bogdan M. Wilamowski
• 21.1 Introduction A sensor is a device that provides an electrical output responding to a stimulation of a nonelectrical
• HSI2011 Yokohama. Japan. May 19-21. 2011 Can computers be more intelligent
• 6.1 Introduction Different neural network architectures are widely described in the literature [W89,Z95,W96,WJK99,
• 20.1 Introduction Conventional controllers, such as PID controller, are broadly used for linear processes. In real life, most
• e bipolar junction transistor (BJT) is historically the first solid-state analog amplifier and digital switch, and formed the basis of integrated circuits (IC) in the 1970s. Starting in the early 1980s, the
• 384 JOURNAL OF MICROELECTROMECHANICAL SYSTEMS, VOL. 19, NO. 2, APRIL 2010 Monolithically Integrated Gas Distribution
• 18.1 Introduction The traditional approach to the small-signal analysis of transistor amplifiers employs the transistor
• 12.1 Introduction A sensor is used to transform a nonelectrical stimulation to an electrical response that is suitable to
• 10.1 Introduction Parity-N problems have been studied deeply in many literatures [WH03,HLS99]. The N-bit parity func-
• 10.1 Introduction ere are several different types of field effect transistors (FETs), each of which has a different opera-
• 11.1 Introduction Noise (a spontaneous fluctuation in current or in voltage) is generated in all semiconductor devices.
• 60.1 Introduction Transmission control protocol (TCP) is a part of TCP/Internet protocol (IP) suite [STD7,C02-1,F10,
• 26.1 Introduction Analog filters are essential in many different systems that electrical engineers are required to design
• A Tunable CMOS Resistor with Wide Tuning Range for Low Pass Filter Application
• Special Neural Network Architectures for Easy Electronic Implementations
• 65.1 Introduction With the tremendous growth in available information to the masses, the question is how users can
• HSI 2011 Yokohama, Japan, May 19-21, 2011 Abstract. Neural network research over the past 3 decades
• Advanced Learning Algorithms Bogdan M. Wilamowski
• 978-1-4244-3960-7/09/ $25.00 2009 IEEE 109 HSI 2009 Catania, Italy, May 21-23, 2009
• HSI 2011 Yokohama, Japan, May 19-21, 2011 Abstract. The paper presents the design of three types of
• e pn semiconductor junctions exhibit nonlinear currentvoltage characteristics and they are used to rectify and shape electrical signals. Exponential currentvoltage characteristics are sometimes used
• Figure 2. An example implementation of the third-order lowpass Butterworth ladder filter.
• 63.1 Introduction A static Web site, which is generally written in HTML, does not provide functionality to dynamically
• 13.1 Introduction Since the development of EBP--error backpropagation--algorithm for training neural networks, many
• C++ Implementation of Neural Networks Trainer Hao Yu* and Bogdan M. Wilamowski*
• Bright and dark sides of computational intelligence
• Advantages and problems of soft computing Bogdan M. Wilamowski
• NeuralNetworkTrainingwith SecondOrder H. Yu andB.M. Wilamowski
• Abstract--The number of computer based functions embedded in vehicles has increased significantly in the past two decades. An
• 5438 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 58, NO. 12, DECEMBER 2011 Advantages of Radial Basis Function Networks
• Abstract--The paper presents the state-of-the-art study on the recently published literatures subjected to
• Abstract--The quality of journals is primarily related to the number of citation of published papers. Various measures of
• ComputingUtilizationvia ComputerNetworks N. Phamt,B.M. Wilamowskir, andA. Malinowski2
• Comparisonof FuzzyandNeural Systemsfor Implementationof NonlinearControlSurfaces
• Abstract--The paper presents the state-of-the-art study on the recently published literatures subjected to power aware design in