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DAQ and data processing is a basic part of all automated production systems, diagnostic systems, watching over quality of production, energy distribution, transport control or in various other areas. Demands on the speed, accuracy and reliability increase in general. It is possible to achieve not only using superior (but also more expensive) hardware, but also applying advanced data acquisition and intelligent data processing. It deals e.g. optimal data fusion of a number of sensors, new stochastic methods for accuracy increasing, new algorithms for acceleration of data processing, etc. These are the grounds for publishing this book. Advanced Data Acquisition and Intelligent Data Processing offers 10 up-to-date examples of different applications of advanced data acquisition and intelligent data processing used in monitoring, measuring and diagnostics systems. The book arose based on the most interesting papers from this area published at IDAACS?2013 conference. However, the indivudual chapters include not only designed solution in wider context but also relevant theoretical parts, achieved results and possible future ways.
Technical topics discussed in this book include:
advanced methods of data acquisition in application that are not routine
measured data fusion using up-to-date advanced data processing
nonlinear dynamical systems identification
multidimensional image processing.Advanced Data Acquisition and Intelligent Data Processing is ideal for personnel of firms deals with advanced instrumentation, energy consumption monitoring, environment monitoring, non-descructive diagnostics robotics, etc., as well as academic staff and postgraduate students in electrical, control and computer engineering.
Introduction
Waveform Acquisition with Resolutions Exceeding those of the ADCs Employed
Different Appliance Identification in Non-Intrusive Appliance Load Monitoring
Design and Testing of an Electronic Nose Sensitive to the Aroma of Truffles
DAQ Acquisition for Ultrasonic Transducer Evaluation Under Spread Spectrum Excitation
Optimal Information Fusion in Stochastic Unknown Input Observers Network
Odor Classification By Neural Networks
ANFIS Based Approach for Improved Multisensors Signal Processing
FPGA-Based ANFIS Linearizer for Measurement Systems
Identification of Systems Using Volterra Model in Time and Frequency Domain
Training Cellular Automata for Hyperspectral Image Segmentation
Index