TY  - JOUR
AU  - Jakšić, Zoran
AU  - Devi, Swagata
AU  - Jakšić, Olga
AU  - Guha, Koushik
PY  - 2023
UR  - https://cer.ihtm.bg.ac.rs/handle/123456789/7202
AB  - The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. Because of that, in spite of the fact that there are a lot of surveys and reviews in the field, they quickly become dated. Thus, it is of importance to keep pace with the current developments. In this review, we first consider a possible classification of bio-inspired multiparameter optimization methods because papers dedicated to that area are relatively scarce and often contradictory. We proceed by describing in some detail some more prominent approaches, as well as those most recently published. Finally, we consider the use of biomimetic algorithms in two related wide fields, namely microelectronics (including circuit design optimization) and nanophotonics (including inverse design of structures such as photonic crystals, nanoplasmonic configurations and metamaterials). We attempted to keep this broad survey self-contained so it can be of use not only to scholars in the related fields, but also to all those interested in the latest developments in this attractive area.
PB  - MDPI
T2  - Biomimetics
T1  - A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics
VL  - 8
IS  - 3
SP  - 278
DO  - 10.3390/biomimetics8030278
ER  - 

@article{
author = "Jakšić, Zoran and Devi, Swagata and Jakšić, Olga and Guha, Koushik",
year = "2023",
abstract = "The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. Because of that, in spite of the fact that there are a lot of surveys and reviews in the field, they quickly become dated. Thus, it is of importance to keep pace with the current developments. In this review, we first consider a possible classification of bio-inspired multiparameter optimization methods because papers dedicated to that area are relatively scarce and often contradictory. We proceed by describing in some detail some more prominent approaches, as well as those most recently published. Finally, we consider the use of biomimetic algorithms in two related wide fields, namely microelectronics (including circuit design optimization) and nanophotonics (including inverse design of structures such as photonic crystals, nanoplasmonic configurations and metamaterials). We attempted to keep this broad survey self-contained so it can be of use not only to scholars in the related fields, but also to all those interested in the latest developments in this attractive area.",
publisher = "MDPI",
journal = "Biomimetics",
title = "A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics",
volume = "8",
number = "3",
pages = "278",
doi = "10.3390/biomimetics8030278"
}

Jakšić, Z., Devi, S., Jakšić, O.,& Guha, K.. (2023). A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics. in Biomimetics
MDPI., 8(3), 278.
https://doi.org/10.3390/biomimetics8030278

Jakšić Z, Devi S, Jakšić O, Guha K. A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics. in Biomimetics. 2023;8(3):278.
doi:10.3390/biomimetics8030278 .

Jakšić, Zoran, Devi, Swagata, Jakšić, Olga, Guha, Koushik, "A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics" in Biomimetics, 8, no. 3 (2023):278,
https://doi.org/10.3390/biomimetics8030278 . .

TY  - JOUR
AU  - Devi, Swagata
AU  - Guha, Koushik
AU  - Jakšić, Olga
AU  - Baishnab, Krishna Lal
AU  - Jakšić, Zoran
PY  - 2022
UR  - https://cer.ihtm.bg.ac.rs/handle/123456789/5373
AB  - This work is dedicated to parameter optimization for a self-biased amplifier to be used in preamplifiers for the diagnosis of seizures in neuro-diseases such as epilepsy. For the sake of maximum compactness, which is obligatory for all implantable devices, power is to be supplied by a piezoelectric nanogenerator (PENG). Several meta-heuristic optimization algorithms and an ANN (artificial neural network)-assisted goal attainment method were applied to the circuit, aiming to provide us with the set of optimal design parameters which ensure the minimal overall area of the preamplifier. These parameters are the slew rate, load capacitor, gain–bandwidth product, maximal input voltage, minimal input voltage, input voltage, reference voltage, and dissipation power. The results are re-evaluated and compared in the Cadence 180 nm SCL environment. It has been observed that, among the metaheuristic algorithms, the whale optimization technique reached the best values at low computational cost, decreased complexity, and the highest convergence speed. However, all metaheuristic algorithms were outperformed by the ANN-assisted goal attainment method, which produced a roughly 50% smaller overall area of the preamplifier. All the techniques described here are applicable to the design and optimization of wearable or implantable circuits.
PB  - Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)
T2  - Micromachines
T1  - Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method
VL  - 13
VL  - 7
SP  - 1104
DO  - 10.3390/mi13071104
ER  - 

@article{
author = "Devi, Swagata and Guha, Koushik and Jakšić, Olga and Baishnab, Krishna Lal and Jakšić, Zoran",
year = "2022",
abstract = "This work is dedicated to parameter optimization for a self-biased amplifier to be used in preamplifiers for the diagnosis of seizures in neuro-diseases such as epilepsy. For the sake of maximum compactness, which is obligatory for all implantable devices, power is to be supplied by a piezoelectric nanogenerator (PENG). Several meta-heuristic optimization algorithms and an ANN (artificial neural network)-assisted goal attainment method were applied to the circuit, aiming to provide us with the set of optimal design parameters which ensure the minimal overall area of the preamplifier. These parameters are the slew rate, load capacitor, gain–bandwidth product, maximal input voltage, minimal input voltage, input voltage, reference voltage, and dissipation power. The results are re-evaluated and compared in the Cadence 180 nm SCL environment. It has been observed that, among the metaheuristic algorithms, the whale optimization technique reached the best values at low computational cost, decreased complexity, and the highest convergence speed. However, all metaheuristic algorithms were outperformed by the ANN-assisted goal attainment method, which produced a roughly 50% smaller overall area of the preamplifier. All the techniques described here are applicable to the design and optimization of wearable or implantable circuits.",
publisher = "Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)",
journal = "Micromachines",
title = "Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method",
volume = "13, 7",
pages = "1104",
doi = "10.3390/mi13071104"
}

Devi, S., Guha, K., Jakšić, O., Baishnab, K. L.,& Jakšić, Z.. (2022). Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method. in Micromachines
Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)., 13, 1104.
https://doi.org/10.3390/mi13071104

Devi S, Guha K, Jakšić O, Baishnab KL, Jakšić Z. Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method. in Micromachines. 2022;13:1104.
doi:10.3390/mi13071104 .

Devi, Swagata, Guha, Koushik, Jakšić, Olga, Baishnab, Krishna Lal, Jakšić, Zoran, "Optimized Design of a Self-Biased Amplifier for Seizure Detection Supplied by Piezoelectric Nanogenerator: Metaheuristic Algorithms versus ANN-Assisted Goal Attainment Method" in Micromachines, 13 (2022):1104,
https://doi.org/10.3390/mi13071104 . .