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Blaise Ravelo

Researcher at Nanjing University of Information Science and Technology

Publications -  233
Citations -  2399

Blaise Ravelo is an academic researcher from Nanjing University of Information Science and Technology. The author has contributed to research in topics: Group delay and phase delay & Microstrip. The author has an hindex of 21, co-authored 196 publications receiving 1727 citations. Previous affiliations of Blaise Ravelo include École Supérieure d'Ingénieurs en Génie Électrique & Nanjing University.

Papers
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Kron–Branin modelling of ultra-short pulsed signal microelectrode

TL;DR: In this article, an uncommon circuit modeling of microelectrode for ultra-short signal propagation is developed, which is based on the Tensorial Analysis of Network (TAN) using the Kron-Branin (KB) formalism.
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Theory and Original Design of Resistive-Inductive Network High-Pass Negative Group Delay Integrated Circuit in 130-nm CMOS Technology

TL;DR: In this paper , an original design method of high-pass (HP) negative group delay (NGD) integrated circuit (IC) is developed based on a passive topology which is essentially composed of resistor-inductor (RL) network.
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Bandpass NGD function design for 5G microwave signal delay synchronization application

TL;DR: A design method of simple bandpass (BP) negative group delay (NGD) topology that can be useful for the improvement of phase linearity and GD equalization of future 5G microwave devices is introduced.
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130‐nm BiCMOS design of low‐pass negative group delay integrated RL‐circuit

TL;DR: In this paper , a low-pass negative group delay (NGD) integrated circuit (IC) implemented in 130nm BiCMOS technology is investigated, which is composed by RL-network with high Ohmic unsalicided N+poly resistor and symmetrical high current spiral inductor.
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All-Pass NGD FIR Original Study for Sensor Failure Detection Application

TL;DR: In this paper , a finite impulse response (FIR) with an all-pass negative group delay (AP-NGD) circuit is described, and the potential industrial application of the NGD predictor for sensor fault diagnosis in real-time is described.