Design of an Inverter-based 3<SUP>rd</SUP> Order ∆Σ CMOS Modulator using a 1.5 bit Comparator and Analog Adder

The paper deals with the application of a newly developed anemometer without moving parts. It is digitized and has built-in electronics that convert the vibrations of two aluminum fixed frames into two digital signals: one, which shows the strength (speed absolute value)) of the wind, and the other, which shows its direction. Both of these signals are used to calculate wind power and energy. Earlier works have shown that the two-bit stochastic digital measurement method overcomes (eliminates) the problem of the offset of the analog adder. The authors of this paper apply this idea to the digital output of the sensor, where the role of the offset of the analog adder is taken over by the integral nonlinearity of the digital output of the anemometer. The first step in this direction is digitally dithering the sensor output. This principle is presented in detail, as well as a rough estimate of the accuracy gain in measuring wind energy. The obtained result shows that the accuracy in measuring wind energy is not worse than the limit accuracy in the case of a cup anemometer that generates sinusoidal voltage.

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Metabolic Perceptrons for Neural Computing in Biological Systems

10.1101/616599 ◽

2019 ◽

Author(s):

Amir Pandi ◽

Mathilde Koch ◽

Peter L Voyvodic ◽

Paul Soudier ◽

Jerome Bonnet ◽

...

Keyword(s):

Gene Expression Regulation ◽

Binary Classification ◽

Neural Computing ◽

New Approach ◽

Multiple Input ◽

Computer Aided ◽

Biological Computation ◽

Biological Circuits ◽

Analog Adder

AbstractSynthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a new approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model trained on experimental data, we finally implement two four-input “perceptrons” for desired binary classification of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

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analog adder

10.1007/springerreference_8015 ◽

2011 ◽

Keyword(s):

Analog Adder

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A spiking-neuron collective analog adder with scalable precision

2013 IEEE International Symposium on Circuits and Systems (ISCAS2013) ◽

10.1109/iscas.2013.6572172 ◽

2013 ◽

Cited By ~ 1

Author(s):

Sung Sik Woo ◽

Rahul Sarpeshkar

Keyword(s):

Spiking Neuron ◽

Analog Adder

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Data-rate-efficient CMOS modulator for wireless biomedical sensor network applications

International Journal of Microwave and Wireless Technologies ◽

10.1017/s1759078715001361 ◽

2015 ◽

Vol 9 (1) ◽

pp. 1-8

Author(s):

Kai-Wen Yao ◽

Cihun-Siyong Alex Gong ◽

Yu-Ting Hsueh ◽

Yu-Lin Tsou ◽

Muh-Tian Shiue ◽

...

Keyword(s):

Sensor Network ◽

Frequency Synthesizer ◽

Low Complexity ◽

Area Network ◽

Body Area ◽

Network Systems ◽

Network Applications ◽

Biomedical Sensor ◽

Shift Keying ◽

Analog Adder

A 0.18 µm CMOS Binary Frequency Shift Keying Modulator with a novel frequency synthesizer structure is proposed in this paper. Based on an analog adder technique being the backbone of the synthesizer, this prototype demonstrates a compact modulator with low complexity, which achieves 1 Mbps at 400 MHz while dissipating 3.1 mW at 1.5 V supply. The proposed design is ideal for biomedical sensor network systems including distributed wearable body area network.

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