Dynamic range extension technique for high-order ADCs by digital level control

1997 ◽  
Vol 33 (25) ◽  
pp. 2094 ◽  
Author(s):  
Dong-Yun Lee ◽  
Min-Kyu Kim ◽  
Dae-Yun Shim ◽  
Wonchan Kim
Keyword(s):  
Dynamic Range ◽  
High Order ◽  
Range Extension ◽  
Level Control

Dynamic range extension technique for high-order sigma delta ADCS by digital level control

1999 ◽  
Vol 21 (2) ◽  
pp. 98
Author(s):  
Dong-Yun Lee ◽  
Min-Kyu Kim ◽  
Dae-Yun Shim ◽  
Wonchan Kim
Keyword(s):  
Dynamic Range ◽  
High Order ◽  
Range Extension ◽  
Level Control ◽  
Sigma Delta

A dynamic range extension system for LHAASO WCDA-1

2021 ◽  
Author(s):  
F. Aharonian ◽  
Q. An ◽  
Axikegu ◽  
L. X. Bai ◽  
Y. X. Bai ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Range Extension ◽  
Extension System

scholarly journals Asymmetric high-order anatomical brain connectivity sculpts effective connectivity

2020 ◽  
Vol 4 (3) ◽  
pp. 871-890
Author(s):  
Arseny A. Sokolov ◽  
Peter Zeidman ◽  
Adeel Razi ◽  
Michael Erb ◽  
Philippe Ryvlin ◽  
...  
Keyword(s):  
White Matter ◽  
Dynamic Range ◽  
Diffusion Processes ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Structural Connectivity ◽  
Laplacian Matrix ◽  
Graph Laplacian ◽  
Brain Regions ◽  
High Order

Bridging the gap between symmetric, direct white matter brain connectivity and neural dynamics that are often asymmetric and polysynaptic may offer insights into brain architecture, but this remains an unresolved challenge in neuroscience. Here, we used the graph Laplacian matrix to simulate symmetric and asymmetric high-order diffusion processes akin to particles spreading through white matter pathways. The simulated indirect structural connectivity outperformed direct as well as absent anatomical information in sculpting effective connectivity, a measure of causal and directed brain dynamics. Crucially, an asymmetric diffusion process determined by the sensitivity of the network nodes to their afferents best predicted effective connectivity. The outcome is consistent with brain regions adapting to maintain their sensitivity to inputs within a dynamic range. Asymmetric network communication models offer a promising perspective for understanding the relationship between structural and functional brain connectomes, both in normalcy and neuropsychiatric conditions.

A Dynamic Range Extension Technique for CMOS Image Sensors With In-Pixel Dual Exposure Synthesis

2015 ◽  
Vol 15 (6) ◽  
pp. 3265-3273 ◽  
Author(s):  
Zhiyuan Gao ◽  
Suying Yao ◽  
Congjie Yang ◽  
Jiangtao Xu
Keyword(s):  
Dynamic Range ◽  
Image Sensors ◽  
Range Extension ◽  
Cmos Image Sensors

scholarly journals Supercritical dynamics at the edge-of-chaos underlies optimal decision-making

2021 ◽  
Author(s):  
Adrián Fernández Amil ◽  
Paul F.M.J. Verschure
Keyword(s):  
Phase Transition ◽  
Decision Making ◽  
Dynamic Range ◽  
High Order ◽  
Optimal Decision ◽  
Inhibitory Interneurons ◽  
Persistent Activity ◽  
Perceptual Decision Making ◽  
Edge Of Chaos ◽  
Cortical Hierarchy

Abstract Critical dynamics, characterized by scale-free neuronal avalanches, is thought to underlie optimal function in the sensory cortices by maximizing information transmission, capacity, and dynamic range. In contrast, deviations from criticality have not yet been considered to support any cognitive processes. Nonetheless, neocortical areas related to working memory and decision-making seem to rely on long-lasting periods of ignition-like persistent firing. Such firing patterns are reminiscent of supercritical states where runaway excitation dominates the circuit dynamics. In addition, a macroscopic gradient of the relative density of Somatostatin (SST+) and Parvalbumin (PV+) inhibitory interneurons throughout the cortical hierarchy has been suggested to determine the functional specialization of low- versus high-order cortex. These observations thus raise the question of whether persistent activity in high-order areas results from the intrinsic features of the neocortical circuitry. We used an attractor model of the canonical cortical circuit performing a perceptual decision-making task to address this question. Our model reproduces the known saddle-node bifurcation where persistent activity emerges, merely by increasing the SST+/PV+ ratio while keeping the input and recurrent excitation constant. The regime beyond such a phase transition renders the circuit increasingly sensitive to random fluctuations of the inputs -i.e., chaotic-, defining an optimal SST+/PV+ ratio around the edge-of-chaos. Further, we show that both the optimal SST+/PV+ ratio and the region of the phase transition decrease monotonically with increasing input noise. This suggests that cortical circuits regulate their intrinsic dynamics via inhibitory interneurons to attain optimal sensitivity in the face of varying uncertainty. Hence, on the one hand, we link the emergence of supercritical dynamics at the edge-of-chaos to the gradient of the SST+/PV+ ratio along the cortical hierarchy, and, on the other hand, explain the behavioral effects of the differential regulation of SST+ and PV+ interneurons by neuromodulators like acetylcholine in the presence of input uncertainty.

scholarly journals The dynamic range extension system for the LHAASO-WCDA experiment

2017 ◽  
Author(s):  
Cheng LIU ◽  
Mingjun Chen ◽  
Xiaohan Ding ◽  
Wenyan Du ◽  
Bo Gao ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Range Extension ◽  
Extension System
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