Carretera Ensenada Tijuana No. 3918
Carretera Ensenada Tijuana No. 3918
Weber M.,Carrera 80 No. 65 223 |
Altenberger U.,Karl Liebknecht Str. 24 |
Lopez-Martinez M.,Carretera Ensenada Tijuana No 3918 |
Tobon M.,Carrera 80 No. 65 223 |
And 3 more authors.
Geologica Acta | Year: 2011
The chemical composition of eclogites, found as boulders in a Tertiary conglomerate from the Guajira Peninsula, Colombia suggests that these rocks are mainly metamorphosed basaltic andesites. They are depleted in LILE elements compared to MORB, have a negative Nb-anomaly and flat to enriched REE patterns, suggesting that their protoliths evolved in a subduction related tectonic setting. They show island-arc affinities and are similar to primitive islandarc rocks described in the Caribbean. The geochemical characteristics are comparable to low-grade greenschists from the nearby Etpana Terrane, which are interpreted as part of a Cretaceous intra-oceanic arc. These data support evidence that the eclogites and the Etpana terrane rocks formed from the same volcano-sedimentary sequence. Part of this sequence was accreted onto the margin and another was incorporated into the subduction channel and metamorphosed at eclogite facies conditions. 40Ar-39Ar ages of 79.2±1.1Ma and 82.2±2.5Ma determined on white micas, separated from two eclogite samples, are interpreted to be related to the cooling of the main metamorphic event. The formation of a common volcano-sedimentary protolith and subsequent metamorphism of these units record the ongoing Late Cretaceous continental subduction of the South American margin within the Caribbean intra-oceanic arc subduction zone. This gave way to an arc-continent collision between the Caribbean and the South American plates, where this sequence was exhumed after the Campanian.
Montano O.,Carretera Ensenada Tijuana No. 3918 |
Orlov Y.,Carretera Ensenada Tijuana No. 3918 |
Aoustin Y.,L'IRCCyN |
Autonomous Robots | Year: 2016
The primary concern of the work is robust control of hybrid mechanical systems under unilateral constraints with underactuation degree one. Nonlinear (Formula presented.) output feedback synthesis is developed in the hybrid setting, covering collision phenomena. Sufficient conditions are presented to ensure internal asymptotic stability while also attenuating external disturbances and plant uncertainties. The developed synthesis is applied to the orbital stabilization of an underactuated bipedal robot periodically touching the ground. Good performance of the closed-loop system is obtained not only in the presence of measurement noise and external disturbances, affecting the gait of the biped between collision time instants, but also under uncertainties at the velocity restitution when the ground collision occurs. © 2016 Springer Science+Business Media New York
Fimbres-Castro C.,UABC |
Alvarez-Borrego J.,Carretera Ensenada Tijuana No. 3918
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013
In this work a new methodology to recognize objects is presented. This system is invariant to position, rotation and scale by using identity vectors signatures Is obtained for both the target and the problem image. In this application, Is are obtained by means of a simplification of the main features of the original image in addition of the properties of the Fourier transform. The nonlinear correlation by using a kth law is used to obtain the digital correlation providing information on the similarity between different objects besides their great capacity to discriminate them even when are very similar. This new methodology recognizes objects in a more simple way providing a significant reduction of the image information of size m x n to one-dimensional vector of 1 x 256 consequently with low computational cost of approximately 0.02 s per image. In addition, the statistics of Euclidean distances is used as an alternative methodology for comparison of identity vectors signatures. Also, experiments were carried out in order to find the noise tolerance. The invariant to position, rotation and scale of this digital system was tested with different species of fish (real images). The results obtained have a confidence level above 95.4%. © 2013 SPIE.
Torres V.M.,Carretera Ensenada Tijuana No. 3918 |
Castillo O.,Tijuana Institute of Technology
Studies in Computational Intelligence | Year: 2015
This paper presents a type-2 adaptive fuzzy neural network ensemble to predict chaotic time series in combination with the well known M8 algorithm. The chaotic time series is depicted by the register of seismic events and their seismic coordinates in a catalog. ANFIS model are used as components of the Ensemble to train and evaluate seven chaotic time series that are used by the M8 algorithm to make a prediction. © Springer International Publishing Switzerland 2015.
Diaz-Ramirez V.H.,National Polytechnic Institute of Mexico |
Campos-Trujillo O.G.,National Polytechnic Institute of Mexico |
Kober V.,Carretera Ensenada Tijuana No. 3918 |
Aguilar-Gonzalez P.M.,Carretera Ensenada Tijuana No. 3918
Optical Engineering | Year: 2012
An efficient method for reliable multiclass pattern recognition using a bank of adaptive correlation filters is proposed. The method can recognize and classify multiple targets from an input scene by using both the intensity and phase distributions of the output complex correlation plane. The adaptive filters are synthesized with the help of an iterative algorithm based on synthetic discriminant functions with complex constraints. The algorithm optimizes the discrimination capability of the adaptive filters and determines the minimum number of filters in a bank to guarantee a desired classification efficiency. As a result, the computational complexity of the proposed system is low. Computer simulation results obtained with the proposed approach in cluttered and noisy scenes are discussed and compared with those obtained through existing methods in terms of recognition performance, classification efficiency, and computational complexity. © 2012 Society of Photo-Optical Instrumentation Engineers (SPIE).