Nonlinearity Estimation of Digital Signals

2020 ◽  
pp. 69-80
Author(s):  
Kiril Alexiev
Keyword(s):  
Digital Signals ◽  
Nonlinearity Estimation

A Python application to generate digital signals

2020 ◽  
Vol 65 (1) ◽  
pp. 96-104
Author(s):  
Tatian-Cristian Mălin
Keyword(s):  
Numerical Simulation ◽  
Programming Language ◽  
Digital Signals ◽  
Python Programming Language ◽  
Python Programming

We introduce in this paper an application developed in the Python programming language that can be used to generate digital signals with known frequencies and amplitudes. These digital signals, since have known parameters, can be used to create benchmarks for test and numerical simulation.

Confirming the Signal Integrity in Transmission of Digital Signals on Microstrip Straight Circuits via the Eye Diagrams

2014 ◽  
Vol 5 (1) ◽  
pp. 737-741
Author(s):  
Alejandro Dueñas Jiménez ◽  
Francisco Jiménez Hernández
Keyword(s):  
Integrated Circuits ◽  
Printed Circuit Board ◽  
Signal Integrity ◽  
High Volume ◽  
Information Storage ◽  
Circuit Board ◽  
Electromagnetic Simulation ◽  
Electronic Systems ◽  
Digital Signals ◽  
Printed Circuit

Because of the high volume of processing, transmission, and information storage, electronic systems presently requires faster clock speeds tosynchronizethe integrated circuits. Presently the “speeds” on the connections of a printed circuit board (PCB) are in the order of the GHz. At these frequencies the behavior of the interconnects are more like that of a transmission line, and hence distortion, delay, and phase shift- effects caused by phenomena like cross talk, ringing and over shot are present and may be undesirable for the performance of a circuit or system.Some of these phrases were extracted from the chapter eight of book “2-D Electromagnetic Simulation of Passive Microstrip Circuits” from the corresponding author of this paper.

Modeling RF Digital Signals for Communications Applications

2009 ◽  
Author(s):  
Amalia E. Barrios ◽  
Veena Gadwal ◽  
Richard Sprague
Keyword(s):  
Digital Signals

scholarly journals A Pixel Design of a Branching Ultra-Highspeed Image Sensor

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2506
Author(s):  
Nguyen Hoai Ngo ◽  
Kazuhiro Shimonomura ◽  
Taeko Ando ◽  
Takayoshi Shimura ◽  
Heiji Watanabe ◽  
...  
Keyword(s):  
Image Sensor ◽  
Frame Rate ◽  
Front Side ◽  
Digital Signals ◽  
Memory Element ◽  
Image Capture ◽  
Readout Circuits ◽  
Pros And Cons ◽  
Very High

A burst image sensor named Hanabi, meaning fireworks in Japanese, includes a branching CCD and multiple CMOS readout circuits. The sensor is backside-illuminated with a light/charge guide pipe to minimize the temporal resolution by suppressing the horizontal motion of signal carriers. On the front side, the pixel has a guide gate at the center, branching to six first-branching gates, each bifurcating to second-branching gates, and finally connected to 12 (=6×2) floating diffusions. The signals are either read out after an image capture operation to replay 12 to 48 consecutive images, or continuously transferred to a memory chip stacked on the front side of the sensor chip and converted to digital signals. A CCD burst image sensor enables a noiseless signal transfer from a photodiode to the in-situ storage even at very high frame rates. However, the pixel count conflicts with the frame count due to the large pixel size for the relatively large in-pixel CCD memory elements. A CMOS burst image sensor can use small trench-type capacitors for memory elements, instead of CCD channels. However, the transfer noise from a floating diffusion to the memory element increases in proportion to the square root of the frame rate. The Hanabi chip overcomes the compromise between these pros and cons.

scholarly journals Optical Axons for Electro-Optical Neural Networks

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6119
Author(s):  
Mircea Hulea ◽  
Zabih Ghassemlooy ◽  
Sujan Rajbhandari ◽  
Othman Isam Younus ◽  
Alexandru Barleanu
Keyword(s):  
Neural Networks ◽  
Optical Signal ◽  
Sensor Data ◽  
Line Of Sight ◽  
Optical Intensity ◽  
Digital Signals ◽  
Link Length ◽  
Optical Neural Networks ◽  
Analogue Signals ◽  
Neural Unit

Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform post-processing of the sensor data. The performance of spiking neural networks has been improved using optical synapses, which offer parallel communications between the distanced neural areas but are sensitive to the intensity variations of the optical signal. For systems with several neuromorphic sensors, which are connected optically to the main unit, the use of optical synapses is not an advantage. To address this, in this paper we propose and experimentally verify optical axons with synapses activated optically using digital signals. The synaptic weights are encoded by the energy of the stimuli, which are then optically transmitted independently. We show that the optical intensity fluctuations and link’s misalignment result in delay in activation of the synapses. For the proposed optical axon, we have demonstrated line of sight transmission over a maximum link length of 190 cm with a delay of 8 μs. Furthermore, we show the axon delay as a function of the illuminance using a fitted model for which the root mean square error (RMS) similarity is 0.95.

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