# Painter, John

## Permanent URI for this collection

This collection contains books, papers, and other research archived by John Painter, Retired Professor of Texas A&M University. Dr. Painter was appointed in three academic departments, being Electrical Engineering, Computer Science, and Aerospace Engineering, commencing in 1974. Prior to coming to Texas A&M, he was an Air Force Officer (Navigator) during the years 1955-1958, and NASA Engineer during 1962-1974.

## News

This Collection is presently UNDER CONSTRUCTION.

## Browse

### Recent Submissions

Item Results on Discrete-Time, Decision-Directed Integrated Detection, Estimation, and Identification(IEEE, 1977-07) Painter, John H.; Jones, S.Show more New results are presented for symbol-by-symbol detection with decision-directed tracking of colored channel disturbances. Recursive sampled-data algorithms are shown for Maximum A Posteriori Probability of detection under colored additive and multiplicative Gaussian noises along with white Gaussian noise. Preliminary evaluation of the algorithms via Monte Carlo simulation shows good performance compared to standard white-noise only algorithms.Show more Item Optimal Symbol-by-Symbol Detection for Duobinary Signaling(IEEE, 1983-09) Eggers, M.; Painter, John H.Show more An optimal symbol-by-symbol detection scheme for duobinary signaling (Class I PRS) which exploits the inherent correlation properties of partial response signaling (PRS) is postulated. Analytical results indicate a maximum improvement of approximately 0.7 dB over conventional split shaping duobinary detection at a 10-4error rate. Although duobinary signaling is emphasized, sufficient generality within the formulation is maintained to accommodate any class of PRS.Show more Item Intelligent system design with fixed-base simulation validation for general aviation(IEEE, 2003-10-05) Rong, Jie; Ding, Yuanyuan; Valasek, J.; Painter, John H.Show more Item On the statistics of the product of a Gaussian noise process and a pseudorandom binary code(IEEE, 1965-12) Painter, John H.Show more Item A combined single sideband hybrid AM-PM signal(IEEE, 1966-07) Painter, John H.Show more Item Single-sideband hybrid AM-PM signal models(IEEE, 1966-03) Painter, John H.Show more Item Comment "On the statistics of the product of a Gaussian process and a pseudo random binary code"(IEEE, 1966-06) Painter, John H.; Jacobs, I.Show more Item Synthesis Techniques for a Class of SSB-AM-PM Signals(IEEE, 1969-05) Painter, John H.Show more This paper develops synthesis techniques for a particular type of single-sideband sinusoidal carrier which is phase modulated by a subcarrier. Mathematical expressions for signal efficiency, sensitivity of design to parameter variation, and ratio of peak to average power are derived and incorporated in a computer program. Given the desired power ratios for modulated signal components, the program solves for the corresponding modulation parameters and evaluates signal efficiency, design sensitivity, and peak to average power ratio. A sample signal design is presented for clarity.Show more Item Symbolic diagnosis for intelligent control(IEEE, 1988-08-24) Painter, John H.; Jowers, S.Show more The results of research intended to create a symbolic diagnostician to support intelligent control of numerical processors and/or processes are reported. Example applications include real-time signal processors, industrial automation, and aerospace power systems. The approach is to create a generic, symbolic inference engine to interpret data from real-time numerical processes. The interpreted data are then utilized by companion symbolic and numeric modules resulting in a dynamic, intelligent real-time control architecture. General results are obtained while focusing research efforts on an initial target application-a software-intensive radio receiver/processor. Object-oriented programming techniques are used due to ease of knowledge engineering and potential parallels to hardware implementation.Show more Item Low cost multi-channel GPS receiver(IEEE, 1988-11-29) Painter, John H.; Tachita, R.; Ikeda, K.; Teranishi, A.; Noe, P.S.Show more An investigation was conducted on compact, multichannel GPS (global positioning system) receivers. The code generator and correlation equipment were simplified, attempting to avoid downgrading the properties possessed by multichannel receivers as much as possible, and the error-increasing factors caused by such modification were examined. As a means of simplifying the receiver hardware, phases with a unit of 1/8 chip were established in the code generator. Each channel was provided with a circuit for determining correlation, and the phase differences of the carrier and the code were measured by time division. It was confirmed that sufficient accuracy of measurement can be obtained even if such simplification is carried out.Show more Item A knowledge-based control paradigm for real-time systems(IEEE, 1988-08-24) Painter, John H.; Lin, S.K.; Glass, E.Show more The authors examine the application of knowledge-based symbolic control to the management of execution and configuration of a complex numerical control system. Symbolic processing is used to implement inference of system state and internal communication for inference and control. The flavor system provides an object-oriented programming environment in which the inference engine and knowledge base for the symbolic controller are realized. System communication is accomplished by asynchronous message passing using a mailbox facility. The particular target application considered is a software-intensive radio, which is envisioned as being digitally implemented. Symbolic processing is used to internally control the radio down to the module level. Testing is via computer emulation (Monte Carlo).Show more Item Reconciling steady-state Kalman and alpha-beta filter design(IEEE, 1990-11) Painter, John H.; Kerstetter, D.; Jowers, S.Show more The deterministic design of the alpha-beta filter and the stochastic design of its Kalman counterpart are placed on a common basis. The first step is to find the continuous-time filter architecture which transforms into the alpha-beta discrete filter via the method of impulse invariance. This yields relations between filter bandwidth and damping ratio and the coefficients, α and β. In the Kalman case, these same coefficients are related to a defined stochastic signal-to-noise ratio and to a defined normalized tracking error variance. These latter relations are obtained from a closed-form, unique, positive-definite solution to the matrix Riccati equation for the tracking error covariance. A nomograph is given that relates the stochastic and deterministic designs.Show more Item Knowledge-based control(IEEE, 1992-03-17) Painter, John H.Show more Knowledge-based control is defined here as the management of dynamic systems whose states admit qualitative modeling. Contributions from several disparate disciplines, such as artificial intelligence, the decision sciences, and fuzzy control, are examined. An aeronautical application is used to illuminate the concepts examined. Two levels of architecture are presented for implementing qualitative decision and control for an aircraft. A geometric rather than algebraic approach is taken to the knowledge-based control problem.Show more Item Fuzzy decision and control, the Bayes context(IEEE, 1993-12-15) Painter, John H.Show more This paper shows how it is that fuzzy control may be viewed as a particular kind of stochastic (Bayesian) control. With the Bayes approach, fuzzy control may be viewed as an ensembled-average control, where the average is taken over a set of competing uncertain antecedent events, predefined on the system state space.Show more Item A fuzzy-tuned adaptive Kalman filter(IEEE, 1993-12-01) Painter, John H.; Young Hwan LhoShow more In this paper, fuzzy processing is applied to the adaptive Kalman filter. The filter gain coefficients are adapted over a 50 dB range of unknown signal/noise dynamics, using fuzzy membership functions. Specific simulation results are shown for a dynamic system model which has position-velocity states, as in vehicle tracking applications such as the global positioning system (GPS). The filter is single-input single-output, driven by measurements of position, corrupted by additive (Gaussian) noise. The fuzzy adaptation technique is also applicable to multiple-input multiple-output applications for the cases where the states are higher-order moments of motion. The fuzzy processing is driven by an inaccurate online estimate of signal-to-noise ratio for the signal being tracked. A robust Bayes scheme calculates the filter gain coefficients from the signal-to-noise estimate. In our implementation, the inaccurate signal-to-noise estimate is corrected by the use of fuzzy membership functions. Performance comparisons are given between optimum, fuzzy-tuned adaptive, and fixed-gain Kalman filters for the second-order position-velocity model.Show more Item Hypertrapezoidal fuzzy membership functions(IEEE, 1996-09-08) Painter, John H.; Kelly, W. E. IIIShow more The authors present a method for representing N-dimensional fuzzy membership functions. The proposed method is a generalization of the one-dimensional trapezoidal membership function commonly used in fuzzy systems. The issue of correlation between input variables and a decrease in the rule base size is the motivation for extending the definition of membership functions into more than one domain. The approach outlined in this paper is focused by practical considerations and use of a Bayesian version of fuzzy logic which requires that set membership sum to one. The fuzzy partitioning which stems from the presented method is parameterized by M+1 values, yielding an efficient mechanism for designing complex fuzzy systems.Show more Item Decision support for the general aviation pilot(IEEE, 1997-10-12) Alcorn, W. P.; Lee, K. A.; Ward, D. T.; Trang, J. A.; Krishnamurthy, K.; Crump, J. W.; Branham, P. A.; Woo, D. L. Y.; Ren-Jye Yu; Robbins, A. C.; Painter, John H.; Kelly, W. E. IIIShow more Increasing air traffic control (ATC) requirements raises the workload of pilots. Required tasks dictate more “head-in-the-cockpit” computation, which can easily distract a pilot from safe airplane operation. Following eight years of research, we present an on-board PC-based computational system that increases pilot situational awareness, decreases diversion to routine computations, and anticipates upcoming needs. The key to anticipatory flight management is an expert system that uses knowledge of ATC procedures, aircraft operating procedures and limitations, and aircraft performance to infer current flight operating “mode” without direct pilot intervention or input. A flight mode interpreter (FMI) enables automatic display selection, pilot advice, and warning. This paper reports the development of an FMI-based flight management system, called General Aviation Pilot Advisory and Training System (GAPATS), that is being developed jointly by Texas A&M University and Knowledge Based Systems, Inc. Software development is carried out using a fixed-base engineering flight simulator. Pilot participation in all phases of development and evaluation is the norm. Flight tests have begun on an instrumented research light twin owned by the Texas A&M University Flight Mechanics Laboratory.Show more