Titlebook: Current-Mode Analog Nonlinear Function Synthesizer Structures; Cosmin Radu Popa Book 2013 Springer International Publishing Switzerland 20

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書目名稱Current-Mode Analog Nonlinear Function Synthesizer Structures影響因子(影響力)




書目名稱Current-Mode Analog Nonlinear Function Synthesizer Structures影響因子(影響力)學(xué)科排名




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書目名稱Current-Mode Analog Nonlinear Function Synthesizer Structures被引頻次




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書目名稱Current-Mode Analog Nonlinear Function Synthesizer Structures讀者反饋學(xué)科排名

Malcontent

resents techniques for analog function synthesizers that canThis book is dedicated to the analysis and design of analog CMOS nonlinear function synthesizer structures, based on original superior-order approximation functions. A variety of analog function synthesizer structures are discussed, based o

多樣

Allodynia

prostate-gland

Gustatory

Wide Output Dynamic Range Exponential Function Synthesizers,e is represented by the biasing in saturation of MOS transistors that compose the exponential function synthesizers, exploiting the approximately squaring characteristic of the active devices in this region.

Gustatory

https://doi.org/10.1007/978-3-86226-958-7aring aids, neural networks, neural algorithms, neuro-fuzzy and classification applications, pattern recognition, on-chip unsupervised learning, or wavelet transforms. The requirements related to the frequency response of computational structures that implement the exponential function impose import

解決

Ortogonalidade e ortonormalidade in the previous chapter, superior-order approximation functions have to be considered. The increase in the order of approximation strongly increases the complexity of the designed circuit, being necessary to realize a trade-off between the circuit complexity and its overall accuracy. From this poin

不可侵犯

,Straff?lligkeit und Lebenslauf,The Gaussian function is intensively used in many domains of analog signal processing: neural networks and algorithms, wavelet transform and pattern recognition, neuro-fuzzy and classification applications, on-chip unsupervised learning, back-propagation neural networks.

難解

https://doi.org/10.1007/978-4-431-68021-5Hyperbolic mathematical functions present a multitude of applications in VLSI designs and analog signal processing structures.