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This paper shows, with a trivial example, how using a Bayesian approach to inference and optimal experimental design it is possible to define a strategy for sensor network querying and movement. The example is oriented towards environmental monitoring problems
The paper presents an improved method for the ADC nonlinearity correction based on a Bayesian filtering approach. In particular, the dependence of the previous method version on the statistic characterization of the input signal has been removed. The proposed improvement has been validated in simulation using behavioural models provided by an ADC producer and on actual ADCs
The paper presents a new method for the correction of non-linearity errors in ADCs. The method has been designed to allow self calibration in systems where an internal signal can be generated, such as base stations for mobile communications. The method has been implemented and tested in simulation on the behavioral model of a commercial ADCs, and on a hardware setup composed by a data acquisition...
To comprehensively understand the fabric pilling phenomena and exactly grade the degree of pilling, the overall fabric surface ruggedness as well as pill characteristics such as pill number, area, and population density should be evaluated with a 3D noncontact scanning system, which obtains 3D surface data with high accuracy. The fractal dimension calculated by a wavelet-fractal method and the standard...
Mapping for mobile robots integrates noisy, spurious sensor data into a single coherent map useful for navigational purposes. The Bayesian framework to mapping is contrasted to the evidential framework, and a sensor model is described for range sensors to work with evidential mapping. The model is simulated and evaluated under varying parameters and in different test environments
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