Optimal CMOS inverter design using differential evolution algorithm

Abstract

Please cite this article in press as: De, B.P., et al., Optimal CMOS inverter design using differential evolution algorithm. J. Electr. Syst. Inform. Technol. (2015), http://dx. AbstractThe inverter is known to be the nucleus of all digital designs. Evolutionary computation may be a competent implement for automatic design of digital integrated circuits (IC). In this paper, optimal switching characteristics of a CMOS inverter are realized using an evolutionary optimization approach called differential evolution (DE) algorithm. The real coded genetic algorithm (RGA) and particle swarm optimization (PSO) have been adopted for the sake of comparison. DE based design results have been compared also with those of the PSPICE results. The comparative simulation results establish the DE as a more competent candidate to other aforementioned evolutionary algorithms in terms of accuracy and convergence speed.

Optimal design of symmetric switching CMOS inverter using symbiotic organisms search algorithm

“…As well known, the fall time (t f ), is the time required for the output voltage to drop from V 90% of the output voltage level down to V 10%, and the rise time (t r ) is defined as the time required for the output voltage to rise from V 10% to V 90%. They can be computed as follows [3][4][5][6][7][8]:…”

“…On the other hand, the high-to-low propagation delay time (t pHL ) is defined as the time delay between the V 50% transition of the rising input voltage and the V 50% transition of the falling output voltage, Lastly, the low-to-high propagation delay time (t pLH ) is defined as the time delay between the V 50% transition of the falling input voltage and the V 50% transition of the rising output voltage, and can be computed as [3][4][5][6][7][8]: The cost (fitness) function to be minimized can be written as [3][4][5][6][7][8]: Subject to the following constraints:…”

“…Performing such a task by hand turns out to be tedious and time consuming. Recently, to make the design more reliable and flexible, different evolutionary optimization algorithms have been used in the design of CMOS inverter with symmetric switching characteristics [1][2][3][4][5][6][7][8]. In [1,2], particle swarm optimization (PSO) was used in the design of a CMOS inverter having symmetrical waveform of output voltage with equal rise time (t r ) and fall time (t f ) and equal propagation delay times (t pHL and t pLH ).…”

“…In [1,2], particle swarm optimization (PSO) was used in the design of a CMOS inverter having symmetrical waveform of output voltage with equal rise time (t r ) and fall time (t f ) and equal propagation delay times (t pHL and t pLH ). In [3][4][5][6][7][8] Specifically, PSO with constriction factor and inertia weight approach (PSOCFIWA), differential evolution (DE), craziness based particle swarm optimization (CRPSO), hybrid harmony search with differential evolution (HS-DE), PSO with aging leader and challenger (ALC-PSO), and firefly algorithm (FA) were applied in [3][4][5][6][7][8], respectively. In each paper, it was shown that the used optimization method gives better results than those presented in [1,2] and those obtained using the real-coded genetic algorithm (RGA).…”

“…The results indicated that SOS gives very good results and is very competitive with the state of the art for the solution of these problems, which motivated this work. The SOS results will be compared with those obtained using different optimization methods available in the literature [3][4][5][6][7]. Moreover, SOS results will be compared with those obtained by the PSPICE simulator.…”