S. Andrew Gadsden

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—Target tracking algorithms are important for a number of applications, including: physics, air traffic control, ground vehicle monitoring, and processing medical images. The probabilistic data association algorithm, in conjunction with the Kalman filter (KF), is one of the most popular and well-studied strategies. The relatively new smooth variable(More)
A multilayered neural network is a multi-input, multi-output (MIMO) nonlinear system in which training can be regarded as a nonlinear parameter estimation problem by estimating the network weights. In this paper, the relatively new smooth variable structure filter (SVSF) is used for the training of a nonlinear multilayered feed forward network. The SVSF is(More)
In this paper, a sliding mode control (SMC) strategy is applied to a pulse width modulation (PWM)-driven pneumatic muscle actuator system using high speed on/off solenoid valves. Servo-pneumatic systems with PWM-driven on/off valves can be used instead of expensive servo valves to decrease complexity, weight, and cost of servo-pneumatic systems. Due to the(More)
A multilayered neural network is a multi-input, multi-output nonlinear system in which network weights can be trained by using parameter estimation algorithms. In this paper, a novel training method is proposed. This method is based on the relatively new smooth variable structure filter (SVSF) and is formulated for feed-forward multilayer perceptron(More)
This paper discusses the undervalued importance of Regularized Least Squares, and its continued usefulness in solving supervised and semi-supervised learning problems. The common two moon classification problem was used to study and compare the effectiveness of three methods: the Support Vector Machine (Radial Basis Functions and 6 th Order Polynomials),(More)
 Abstract— An important area of study for aerospace and electronic systems involves target tracking applications. To successfully track a target, state and parameter estimation strategies are used in conjunction with data association techniques. Even after 50 years, the Kalman filter (KF) remains the most popular and well-studied estimation strategy in the(More)