Parametric shapes model objects as programs producing a geometry based on a few semantic degrees of freedom, called hyper-parameters. These shapes are the typical output of non-destructive modeling, CAD modeling or rigging. However they suffer from the ...

In this paper, a type-2 fuzzy neural network is used to adaptive inverse control of a class of nonlinear systems. The proposed method has proper performance for real-time control of nonlinear and time-invariant systems and has a quick response to ...

This paper presents information processing and representation as an intelligent regulation system. The paper illustrates advanced numerical method in an intelligent control system. The fuzzy membership function allow preserving more quantitative ...

Neural network inverse control is applied to doubly-fed generation system, and the mathematical model of inverse system is derived from the power control model of the doubly-fed induction generator. Through the proper selection of input and output ...

A novel neural approximate inverse control is proposed for general unknown single-input-single-output (SISO) and multi-input-multi-output (MIMO) nonlinear discrete dynamical systems. Based on an innovative input/output (I/O) approximation of neural ...

We describe a method for controlling smoke simulations through user-specified keyframes. To achieve the desired behavior, a continuous quasi-Newton optimization solves for appropriate "wind" forces to be applied to the underlying velocity field ...

We describe a method for controlling smoke simulations through user-specified keyframes. To achieve the desired behavior, a continuous quasi-Newton optimization solves for appropriate "wind" forces to be applied to the underlying velocity field ...

Traditionally, the issues of cost, size, and weight of artificial neural network implementations have not been the primary concern of researchers. These issues are important in many applications such as those required in space travel, high-volume commercial ...