Optimizing High Speed Flip-Flop Using Genetic Algorithm

Aezinia, Fatemeh; Afzali-Kusha, Ali; Lucas, Caro

doi:10.1109/apccas.2006.342165

Cited by 3 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Results from experiments of ACO and GA on four digital circuits of different complexity imply that both ACO and GA produce approximately optimized results, with ACO performing slightly better than GA. GA is used nowadays frequently for optimization of circuits [5][6][7], and it has been found For buffer chain, NAND gate and full adder, ACO and GA results are nearly equal. In smaller fundamental logic circuits (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…In [5] also, NAND gate is optimized using Monte Carlo and GA to minimize the objective function (7). In this work, same objective function is minimized.…”

Section: Three Input Nand Gatementioning

confidence: 99%

“…Similarly, GA has been used in optimizing high speed flip-flop in [7]. Similarly, GA has been used in optimizing high speed flip-flop in [7].…”

mentioning

confidence: 99%

“…In many previous works, transistor size optimization problem has been attempted using GA, and results are good in most of the cases [5][6][7]. In many previous works, transistor size optimization problem has been attempted using GA, and results are good in most of the cases [5][6][7].…”

mentioning

confidence: 99%

“…improvement of 7% in circuit performance and reduction of 44% in power consumption of the circuit is achieved using GA. Similarly, GA has been used in optimizing high speed flip-flop in [7]. Results from the optimized flip-flop show large reduction in power delay product (PDP), as compared to, flip-flop with transistor sizes, without optimization.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Transistor size optimization in digital circuits using ant colony optimization for continuous domain

Gupta

Ghosh

2012

Circuit Theory & Apps

View full text Add to dashboard Cite

In this paper, ant colony optimization (ACO) algorithm is presented, as a tool to find transistor sizes in digital circuits. Performance of ACO has been tested on four digital circuits, of different complexity, to find optimum balance between power and delay of circuits. Optimization problem has been set up by first, formulating an objective function, to be minimized, for each circuit and then finding the values of variables of circuits, using optimization algorithm. For the purpose of examining the results, circuits are optimized using genetic algorithm (GA) also. Results show that, ACO performs better than GA, for all the four circuits, in finding optimized transistor sizes.

show abstract

Section: Discussionmentioning

confidence: 99%

“…In [5] also, NAND gate is optimized using Monte Carlo and GA to minimize the objective function (7). In this work, same objective function is minimized.…”

Section: Three Input Nand Gatementioning

confidence: 99%

“…Similarly, GA has been used in optimizing high speed flip-flop in [7]. Similarly, GA has been used in optimizing high speed flip-flop in [7].…”

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations