# R. Saravanakumar

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/r-saravanakumar/

## Facts

| Field | Value |
| --- | --- |
| Citations | 1,665 |
| Field | Neural Networks Stability and Synchronization |
| h-index | 27 |
| i10-index | 41 |
| Last Known Institution | Shenzhen Technology University |
| OpenAlex ID | https://openalex.org/A5012694572 |
| ORCID iD | 0000-0002-4772-1732 |
| Works | 96 |

## Researcher papers

- [Stability of Markovian Jump Generalized Neural Networks With Interval Time-Varying Delays](https://scholariq.org/papers/stability-of-markovian-jump-generalized-neural-networks-with-interval-time/)
- [Exponential Stability, Passivity, and Dissipativity Analysis of Generalized Neural Networks With Mixed Time-Varying Delays](https://scholariq.org/papers/exponential-stability-passivity-and-dissipativity-analysis-of-generalized-neural/)
- [New passivity criteria for memristor-based neutral-type stochastic BAM neural networks with mixed time-varying delays](https://scholariq.org/papers/new-passivity-criteria-for-memristor-based-neutral-type-stochastic-bam-neural/)
- [Delay-dependent stability criteria of uncertain Markovian jump neural networks with discrete interval and distributed time-varying delays](https://scholariq.org/papers/delay-dependent-stability-criteria-of-uncertain-markovian-jump-neural-networks/)
- [Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme](https://scholariq.org/papers/strict-dissipativity-synchronization-for-delayed-static-neural-networks-an-event/)
- [Finite-Time Passivity-Based Stability Criteria for Delayed Discrete-Time Neural Networks via New Weighted Summation Inequalities](https://scholariq.org/papers/finite-time-passivity-based-stability-criteria-for-delayed-discrete-time-neural/)
- [Less conservative delay-dependent<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si0013.gif" overflow="scroll"><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mo>∞</mml:mo></mml:mrow></mml:msub></mml:math>control of uncertain neural networks with discrete interval and distributed time-varying delays](https://scholariq.org/papers/less-conservative-delay-dependent-mml-math-xmlns-mml-http-www-w3-org-1998-math/)
- [Finite-time synchronization of sampled-data T–S fuzzy complex dynamical networks subject to average dwell-time approach](https://scholariq.org/papers/finite-time-synchronization-of-sampled-data-t-s-fuzzy-complex-dynamical-networks/)
- [Robust<i>H</i><sub>∞</sub>control of uncertain stochastic Markovian jump systems with mixed time-varying delays](https://scholariq.org/papers/robust-i-h-i-sub-sub-control-of-uncertain-stochastic-markovian-jump-systems-with/)
- [<i>H</i><sub>∞</sub> state estimation of generalised neural networks with interval time-varying delays](https://scholariq.org/papers/i-h-i-sub-sub-state-estimation-of-generalised-neural-networks-with-interval-time/)
- [High-Precision Plant Disease Identification Using an Efficientnet-Based Deep Learning Model with Squeeze-and-Excitation](https://scholariq.org/papers/high-precision-plant-disease-identification-using-an-efficientnet-based-deep/)

## Researcher topics

- [Neural Networks Stability and Synchronization](https://scholariq.org/topics/neural-networks-stability-and-synchronization/)
- [Stability and Control of Uncertain Systems](https://scholariq.org/topics/stability-and-control-of-uncertain-systems/)
- [Matrix Theory and Algorithms](https://scholariq.org/topics/matrix-theory-and-algorithms/)
- [Advanced Memory and Neural Computing](https://scholariq.org/topics/advanced-memory-and-neural-computing/)
- [Distributed Control Multi-Agent Systems](https://scholariq.org/topics/distributed-control-multi-agent-systems/)

## Researcher university

- [Shenzhen Technology University](https://scholariq.org/institutions/shenzhen-technology-university/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.