The Cerebellar Model Articulation Controller (CMAC) [1, 2] is a neural network that models the structure and function of the part of the brain known as the cerebellum. The cerebellum provides precise coordination of motor control for such body parts as the eyes, arms, fingers, legs, and wings. It stores and retrieves information required to control thousands of muscles in producing coordinated ...

In this paper, we propose a novel wavelet-based-CMAC (WCMAC) network for predictive image coding. The Gaussian functions of traditional CMAC are replaced by wavelet functions. In addition, properties and advantages of fuzzy TSK-model are used to modify the activation functions of CMAC for obtaining high approximation accuracy and convergent rate. The WCMAC is employed to predict differential pu...

In this section we review the basic operating principles of the CMAC neural network as proposed by Albus [2,4-7]. We then present a mathematical description of the conventional CMAC in a form intended to facilitate software implementation. The notation used is somewhat different than in the original Albus papers, but the set of equations presented is numerically equivalent to the original Albus...

In this section we review the basic operating principles of the CMAC neural network as proposed by Albus [2,4-7]. We then present a mathematical description of the conventional CMAC in a form intended to facilitate software implementation. The notation used is somewhat different than in the original Albus papers, but the set of equations presented is numerically equivalent to the original Albus...

To obtain high-resolution and high-precision images, the aviation remote sensing stabilization platform (ARSSP) is used, which enables isolation of unpredictable aerial camera movements during photography. However, because interaxle coupling interference other nonlinear interferences in ARSSP system, imaging quality adversely affected. Therefore, we derived dynamic model moment between shafts t...

This paper introduces an effective intelligent controller for robotic systems with uncertainties. The proposed method is a novel self-organizing fuzzy cerebellar model articulation (NSOFC) which combination of (CMAC) and sliding mode control (SMC). We also present new Gaussian membership function (GMF) that designed by the prior current GMF each layer CMAC. In addition, relevant data used to ch...

cerebellar model articulation controller neural network is a computational model of cerebellum which acts as a lookup table. the advantages of cmac are fast learning convergence, and capability of mapping nonlinear functions due to its local generalization of weight updating, single structure and easy processing. in the training phase, the disadvantage of some cmac models is unstable phenomenon...

The proliferation of wireless services and applications over the past decade has led to the rapidly increasing demand in wireless spectrum. Hence, we have been facing a critical spectrum shortage problem even though several measurements have indicated that most licensed radio spectrum is very underutilized. These facts have motivated the development of dynamic spectrum access (DSA) and cognitiv...