Search results for: R. K. Nagaria
3 New Design Methodologies for High Speed Low Power XOR-XNOR Circuits
Authors: Shiv Shankar Mishra, S. Wairya, R. K. Nagaria, S. Tiwari
Abstract:
New methodologies for XOR-XNOR circuits are proposed to improve the speed and power as these circuits are basic building blocks of many arithmetic circuits. This paper evaluates and compares the performance of various XOR-XNOR circuits. The performance of the XOR-XNOR circuits based on TSMC 0.18μm process models at all range of the supply voltage starting from 0.6V to 3.3V is evaluated by the comparison of the simulation results obtained from HSPICE. Simulation results reveal that the proposed circuit exhibit lower PDP and EDP, more power efficient and faster when compared with best available XOR-XNOR circuits in the literature.Keywords: Exclusive-OR (XOR), Exclusive-NOR (XNOR), High speed, Low power, Arithmetic Circuits.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28412 Complementary Energy Path Adiabatic Logic based Full Adder Circuit
Authors: Shipra Upadhyay , R. K. Nagaria, R. A. Mishra
Abstract:
In this paper, we present the design and experimental evaluation of complementary energy path adiabatic logic (CEPAL) based 1 bit full adder circuit. A simulative investigation on the proposed full adder has been done using VIRTUOSO SPECTRE simulator of cadence in 0.18μm UMC technology and its performance has been compared with the conventional CMOS full adder circuit. The CEPAL based full adder circuit exhibits the energy saving of 70% to the conventional CMOS full adder circuit, at 100 MHz frequency and 1.8V operating voltage.Keywords: Adiabatic, CEPAL, full adder, power clock
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24451 Genetic Algorithm and Padé-Moment Matching for Model Order Reduction
Authors: Shilpi Lavania, Deepak Nagaria
Abstract:
A mixed method for model order reduction is presented in this paper. The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. The efficiency of the proposed method can be investigated in terms of closeness of the response of reduced order model with respect to that of higher order original model and a comparison of the integral square error as well.
Keywords: Model Order Reduction (MOR), control theory, Markov parameters, time moments, genetic algorithm, Single Input Single Output (SISO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3533