This paper proposes a novel fault estimation observer for both nonlinear descriptor and normal systems, which are subjected simultaneously to actuator faults, sensor faults and unstructured non-parametric uncertainties.
In this paper we introduce BRAND Binary Robust Appearance and Normal Descriptor, a novel descriptor which efficiently combines appearance and geometric information from RGB-D images, that is largely invariant to rotation and scale transformations.
The frequently used autocorrelated descriptors include Moreau-Broto autocorrelation descriptors, normalized Moreau-Broto autocorrelation descriptors and Geary autocorrelation descriptors.
Simulated examples are presented to illustrate the effectiveness of the proposed observer for both descriptor systems and normal systems and have been shown to perform better than some of the existing methods of fault estimation.
In clinics, we need the symptom reports to diagnose personality disorders, while the dimensional/ categorical descriptors such as normal or abnormal personality styles help us to understand further the phenotypic expression of the disorder [ 1].
The result showed a unique relationship between the strength descriptor of the contact normal force and the principal stress ratio.
The recognition rates are comparable to normal Fourier descriptors while the new scheme at the same time offers the option to also deal with broken contours.
This correlation was adopted because the descriptors do not follow normal distributions and we do not presume the existence of linear relationships between them and the RMSDs.
Goldman and Wipke [26], on the other hand, divide the molecular surface [27] into a series of patches (2Å radius) centered on a set of critical points [28] with each patch defined by a geometrically invariant descriptor (the principal curvatures, normals, and the shape index).
The impact of allometric scaling was assessed by using four different basic turn-over models: (1) no scaling, (2) allometric scaling using bodyweight as the size descriptor, (3) allometric scaling using normal fat mass (NFM) as the size descriptor, and (4) allometric scaling using fat free mass (FFM) as the size descriptor.
