1,721,099 research outputs found
A neural network to retrieve atmospheric parameters from infrared high resolution sensor spectra
No full textMMIC active floating gyrator design and accurate modelling
No full textThis paper introduces a novel floating gyrator circuit. The circuit is based on two differential pair stages used as voltage controlled current sources (VCCS). In order to characterize the component, an accurate passive model is extracted by means of a technique based on symbolic analysis. A prototype has been designed using the Philips ED02AH PHEMT foundry process to validate the proposed mode
A Neural Architecture for the Parameter Extraction of High Frequency Devices
No full textA novel optimization technique for the parameter identification of microwave monolithic integrated circuit is presented. It is based on a hybrid neural network whose learning process convergence allows the validation of the circuit approximated lumped model. The main feature of such a learning process is that no external desired signal is required and the neural network can be considered of the unsupervised type. Furthermore the neural network output represents the lumped circuit parameter estimation
Effect of Enveloppe Linguale Nocturne on Atypical Swallowing: surface Electromyography and computerized Postural test evaluation.
No full text
IMG O3 retrieval and comparison with TOMS/ADEOS columnar ozone: an analysis based on tropical soundings
No full textThe problem of retrieving atmospheric ozone from satellite-based spectrally resolved radiance in the -absorption band has been addressed in this paper. Different tools, statistical and physical, have been implemented and intercompared and their ability to retrieve total columnar ozone has been checked by further comparison with satellite UV sensors. The study has been based on a suitable set of interferometric monitoring of greenhouse gases, complemented with a set of co-located total columnar ozone observations from total ozone mapping spectrometer
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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