Search results for " Mach"
showing 10 items of 1388 documents
A NEURAL NETWORK PRIMER
1994
Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates independently (in paral lel) the information provided by its synapses in order to evaluate its state of activation. The unit response is then a linear or nonlinear function of its activation. Linear algebra concepts are used, in general, to analyze linear units, with eigenvectors and eigenvalues being the core concepts involved. This analysis makes clear the strong similarity between linear neural networks and the general linear model developed by statisticia…
Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology
2017
[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]MOTIVE; International audience; Designing and building a Data Warehouse (DW), and associated OLAP cubes, are long processes, during which decision-maker requirements play an important role. But decision-makers are not OLAP experts and can find it difficult to deal with the concepts behind DW and OLAP. To support DW design in this context, we propose: (i) a new rapid prototyping methodology, integrating two different DM algorithms, to define dimension hierarchies according to decision-maker knowledge; (ii) a complete UML Profile, to define a DW schema that integrates both the DM algorithms; (iii) a mapping process to transform multidimensional …
Toward more realistic viscosity measurements of tyre rubber–bitumen blends
2014
AbstractThe measurement of rheological properties of the tyre rubber bitumen blends is often challenging due to presence of suspended tyre rubber’s crumbs. Furthermore, the phase separation during the course of measurements makes the viscosity of these non-homogeneous blends difficult to ascertain. In this study, a new dual helical impeller was designed and manufactured to be used with a rotational viscometer in order to have a real-time control of the viscosity while performing a laboratory mixing of the blends. Layer based manufacturing techniques showed to be a convenient method to produce complex shaped impeller prototypes before manufacturing the more expensive stainless steel assembly…
Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Specie…
2018
Recognition of tree species and geospatial information on tree species composition is essential for forest management. In this study, tree species recognition was examined using hyperspectral imagery from visible to near-infrared (VNIR) and short-wave infrared (SWIR) camera sensors in combination with a 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum with a diverse selection of 26 tree species from 14 genera was used as a test area. Aerial hyperspectral imagery and high spatial resolution photogrammetric color imagery were acquired from the test area using unmanned aerial vehicle (UAV) borne sensors. Hyperspectral imagery was processed to calibrated …
Regularization operators for natural images based on nonlinear perception models.
2006
Image restoration requires some a priori knowledge of the solution. Some of the conventional regularization techniques are based on the estimation of the power spectrum density. Simple statistical models for spectral estimation just take into account second-order relations between the pixels of the image. However, natural images exhibit additional features, such as particular relationships between local Fourier or wavelet transform coefficients. Biological visual systems have evolved to capture these relations. We propose the use of this biological behavior to build regularization operators as an alternative to simple statistical models. The results suggest that if the penalty operator take…
Cloud Infrastructure for Skin Cancer Scalable Detection System
2018
Skin cancer diagnostics is one of the medical areas where early diagnostic allows achieving patients’ high survival rate. Typically, skin cancer diagnostic is performed by dermatologist, since the amount of such specialists is limited, mortality rate is high [1]. By creating the low cost and easy to use diagnostic device, it is possible to bring skin cancer diagnostic to primary care physicians and allow to check much more persons and diagnose skin cancer on the early stages. There are several existing devices, that provide skin cancer diagnostics [2]. Most of them process the skin images locally and have limited diagnostic capabilities; some of them send images to dermatologists for manual…
Non-linear System Identification with Composite Relevance Vector Machines
2007
Nonlinear system identification based on relevance vector machines (RVMs) has been traditionally addressed by stacking the input and/or output regressors and then performing standard RVM regression. This letter introduces a full family of composite kernels in order to integrate the input and output information in the mapping function efficiently and hence generalize the standard approach. An improved trade-off between accuracy and sparsity is obtained in several benchmark problems. Also, the RVM yields confidence intervals for the predictions, and it is less sensitive to free parameter selection. Teoría de la Señal y Comunicaciones
Discrete Time Signal Processing Framework with Support Vector Machines
2007
Digital signal processing (DSP) of time series using SVM has been addressed in the literature with a straightforward application of the SVM kernel regression, but the assumption of independently distributed samples in regression models is not fulfilled by a time-series problem. Therefore, a new branch of SVM algorithms has to be developed for the advantageous application of SVM concepts when we process data with underlying time-series structure. In this chapter, we summarize our past, present, and future proposal for the SVM-DSP frame-work, which consists of several principles for creating linear and nonlinear SVM algorithms devoted to DSP problems. First, the statement of linear signal mod…
A Constrained Optimal Model Predictive Control for Mono Inverter Dual Parallel PMSM Drives
2018
The actual trends in the design of AC drives are directed to the reduction of the total weight, volume and cost. Usually, this implies the necessity to adopt new motor topologies and converter architectures. An important role is played by the mono-inverter dual parallel motor (MIDP), which gives the possibility to reduce the total weight and costs of power converters. This paper proposes a novel model predictive control algorithm in order to improve the transient performances of a MIDP used for an overhead carrier. The effectiveness of the proposal control is verified through some numerical simulations.
The influence of the stochastic features of the energy source on the design of an electromagnetic generator
2009
The purpose of this paper is to clarify in a general way how the unavoidable randomness of renewable energy sources influences the magnetic design of electric generator. A general model of electro magnetic generator based on the well known d-q axes analysis is given. The energy source is modelled as a stochastic variable and is included in the equations of the system. The equations are solved and, therefore, the energy output of the system is linked to the random characteristic of the energy source. As a result, the magnetic circuit and the parameters of the generator that maximize the energy extraction can be found and generally linked to the stochastic details of the source.