Ronald H. Brown

发表

Estimation of artificial neural network parameters for nonlinear system identification

T. L. Ruchti, Ronald H. Brown, J. J. Garside, 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

Richard J. Povinelli, George F. Corliss, Ronald H. Brown, 2015, 2015 IEEE Power & Energy Society General Meeting.

Analysis of algorithms for velocity estimation from discrete position versus time data

Ronald H. Brown, Susan C. Schneider, Michael G. Mulligan, 1992, IEEE Trans. Ind. Electron..

Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression †

Richard J. Povinelli, Ronald H. Brown, Gregory Merkel, 2018, Energies.

Torque prediction and maximization strategies for bifilar-wound hybrid step motors

Ronald H. Brown, M. Jaroudi, 1992 .

Identifying extreme cold events using phase space reconstruction

Richard J. Povinelli, George F. Corliss, Ronald H. Brown, 2016, Int. J. Appl. Pattern Recognit..

Kalman based artificial neural network training algorithms for nonlinear system identification

T. L. Ruchti, Ronald H. Brown, J. J. Garside, 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

Switched reluctance motor control with artificial neural networks

A. A. Arkadan, Ronald H. Brown, J. J. Garside, 1997, 1997 IEEE International Electric Machines and Drives Conference Record.

Deep Neural Network Regression for Short-Term Load Forecasting of Natural Gas

Richard J. Povinelli, Ronald H. Brown, Gregory Merkel, 2017 .

Torque prediction for efficient commutation strategy of bifilar hybrid step motors

Ronald H. Brown, Maher Jaroudi, 1989, 20th Annual IEEE Power Electronics Specialists Conference.

Deep Neural Network Regression as a Component of a Forecast Ensemble

Richard J. Povinelli, Ronald H. Brown, Gregory Merkel, 2017 .

Artificial neural network identification of partially known dynamic nonlinear systems

Xin Feng, T. L. Ruchti, Ronald H. Brown, 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

A damping circuit for chopper driven bifilar hybrid step motors

Ronald H. Brown, Krishna Srinivas, 1989, 20th Annual IEEE Power Electronics Specialists Conference.

On direct offline discrete-time identification of the continuous-time elements of an RC electrical network

Ronald H. Brown, J. A. Heinen, E.St.P. Walters, 2001, Proceedings of the 44th IEEE 2001 Midwest Symposium on Circuits and Systems. MWSCAS 2001 (Cat. No.01CH37257).

Modeling torque in a switched reluctance motor for adaptive control purposes using self-organizing neural networks

Xin Feng, T. L. Ruchti, Ronald H. Brown, 1992, [Proceedings 1992] The First IEEE Conference on Control Applications.

Step Motor Drives

Ronald H. Brown, 2001 .

Estimation of system arterial parameters for control of an electrically actuated total artificial heart

Xin Feng, T. L. Ruchti, Ronald H. Brown, 1989, Proceedings of the 32nd Midwest Symposium on Circuits and Systems,.

On algorithms for velocity estimation using discrete position encoders

Ronald H. Brown, Susan C. Schneider, J. A. Heinen, 1995, Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics.

Identification of switched reluctance motor states using application specific artificial neural networks

Ronald H. Brown, J. J. Garside, Abd A. Arkadan, 1995, Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics.

Improving Daily Natural Gas Forecasting by Tracking and Combining Models

Richard J. Povinelli, George F. Corliss, Ronald H. Brown, 2017 .

Using self-organizing artificial neural networks for solving uncertain dynamic nonlinear system identification and function modeling problems

T. L. Ruchti, Ronald H. Brown, J. J. Garside, 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

Discrete-time timescale analysis via a new separation ratio and unified approach

D. Subbaram Naidu, Ronald H. Brown, Hardev Singh, 2003, Int. J. Syst. Sci..

On identification of partially known dynamic nonlinear systems with neural network

Xin Feng, T. L. Ruchti, Ronald H. Brown, 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

A parameter estimation approach to artificial neural network weight selection for nonlinear system identification

T. L. Ruchti, Ronald H. Brown, J. J. Garside, 1992, [Proceedings 1992] The First IEEE Conference on Control Applications.

TIME-OPTIMAL ACCELERATION CONTROL AND POINT-TO-POINT CONTROL OF STEP MOTORS

Yan Zhu, Ronald H. Brown, Xin Feng, 1990 .

Nonlinear estimation of torque in switched reluctance motors using grid locking and preferential training techniques on self-organizing neural networks

Xin Feng, T. L. Ruchti, Ronald H. Brown, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

Velocity Observations From Discrete Position Encoders

Ronald H. Brown, Susan C. Schneider, 1987, Other Conferences.

Development of artificial neural network models to predict daily gas consumption

Ronald H. Brown, I. Matin, 1995, Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics.

Diagnostics of Faults in Induction Motor ASDs Using Time-Stepping Coupled Finite Element State-Space and Time Series Data Mining Techniques

Richard J. Povinelli, Nabeel A. O. Demerdash, Ronald H. Brown, 2000 .

Identification algorithm for systemic arterial parameters with application to total artificial heart control

Xin Feng, Timothy L. Ruchti, Ronald H. Brown, 1993, Annals of Biomedical Engineering.

On training artificial neural networks to identify periodic functions

Ronald H. Brown, J. J. Garside, B. S. Behun, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Diagnostics of bar and end-ring connector breakage faults in polyphase induction motors through a novel dual track of time-series data mining and time-stepping coupled FE-state space modeling

Nabeel A. O. Demerdash, Ronald H. Brown, J. F. Bangura, 2001, IEMDC 2001. IEEE International Electric Machines and Drives Conference (Cat. No.01EX485).

Gas load forecasting model input factor identification using a genetic algorithm

Ronald H. Brown, Hui Li Lim, R. Brown, 2001, Proceedings of the 44th IEEE 2001 Midwest Symposium on Circuits and Systems. MWSCAS 2001 (Cat. No.01CH37257).

Identification of dynamic nonlinear systems using artificial neural networks incorporating a priori knowledge

T. L. Ruchti, Ronald H. Brown, 1992, [Proceedings 1992] The First IEEE Conference on Control Applications.

Development of feed-forward network models to predict gas consumption

Xin Feng, Ronald H. Brown, L. P. Piessens, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).