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Sigma Delta A/d Conversion For Signal Conditioning

RRP $68.00

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1.1 Background Moore s Law predicts a decrease by a factor of two in the feature size of CMOS te- nology every three years and has been valid for years. It implies a doubling of the - eration speed and a four times higher transistor count per unit of area, every three years. The combination leads to an eight times higher processing capability per unit of area. This on-going miniaturization allows the integration of complex electronic systems with millions of transistors (Very-Large-Scale-Integration) and enables the integration of el- tronic systems. An electronic system A generic picture of an integrated electronic system is shown in ?g. 1.1. The heart of the system is the signal processing core. This core supports a wide variety of functions, such as customization and programmability of multiple applications, channel coding, the de?nition of the user interface, etc. These functions are enabled by DSP, a controller CPU and various blocks of memory. In advanced ICs these blocks provide (almost) all signal processing and usually dominate in the overall power and area consumption of integrated systems. The huge data rates involved, require high-speed busses for communication between these blocks. A power-management unit fuels the system by providing the - propriate supply voltages and currents."


Computational Models Of Conditioning

RRP $256.99

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Since first described, multiple properties of classical conditioning have been discovered, establishing the need for mathematical models to help explain the defining features. The mathematical complexity of the models puts our understanding of their workings beyond the ability of our intuitive thinking and makes computer simulations irreplaceable. The complexity of the models frequently results in function redundancy, a natural property of biologically evolved systems that is much desired in technologically designed products. Experts provide the latest advancements in the field and present detailed descriptions of how the models simulate conditioned behaviour and its physiological bases. It offers advanced students and researchers examples of how the models are used to analyse existing experimental results and design future experiments. This volume is of great interest to psychologists and neuroscientists, as well as computer scientists and engineers searching for ideas applicable to the design of robots that mimic animal behaviour.


Pavlovian Second-order Conditioning (psychology Revivals)

RRP $381.99

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Originally published in 1980, this volume explores some of the dramatic and exciting changes that had taken place in the field of conditioning in the 15 years prior to publication. The usefulness of a particular learning procedure, second-order conditioning, is explored in three aspects of the learning process: (1) the measurement of learning; (2) the circumstances that produce associative learning; and (3) the content of that learning.

The usefulness of this new paradigm is documented with the results of experiments that had grown out of the author's programmatic work at the time. Completely new results were published for the first time, in an attempt to demonstrate the power of this particular learning procedure in elucidating fundamental questions about the nature of learning.


English (multiple Choice Format): V. 2

RRP $17.99


Computational Models Of Conditioning

RRP $256.99

Click on the Google Preview image above to read some pages of this book!

Since first described, multiple properties of classical conditioning have been discovered, establishing the need for mathematical models to help explain the defining features. The mathematical complexity of the models puts our understanding of their workings beyond the ability of our intuitive thinking and makes computer simulations irreplaceable. The complexity of the models frequently results in function redundancy, a natural property of biologically evolved systems that is much desired in technologically designed products. Experts provide the latest advancements in the field and present detailed descriptions of how the models simulate conditioned behaviour and its physiological bases. It offers advanced students and researchers examples of how the models are used to analyse existing experimental results and design future experiments. This volume is of great interest to psychologists and neuroscientists, as well as computer scientists and engineers searching for ideas applicable to the design of robots that mimic animal behaviour.



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