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  4. A Low Power Reconfigurable LFSR - 2016
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Category: MTech VLSI Projects
By MTech Projects
MTech Projects
01.Jun
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A Low Power Reconfigurable LFSR - 2016

PROJECT TITLE :

A Low Power Reconfigurable LFSR - 2016

ABSTRACT:

Low power has become an important style imperative in the era of nanotechnology. In this paper, we propose a replacement style of energy economical reconfigurable Linear Feedback Shift Registers(LFSRs). The reconfigurable LFSR style allows an increase in the randomness at the output. Furthermore, many low power style techniques are utilized to assist achieve energy savings. This improves the applicability of the planning for security applications in transportable embedded systems. The LFSR building blocks are presented during this paper. The look implementation and analysis were performed using HSPICE. Simulation results show reduction in the energy consumed by the circuit.

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  • Design and Implementation of Area-Efficient and Low-Power Configurable Booth-Multiplier - 2016
  • Design and Implementation of OFDM Transmitter (VHDL)
  • Computing Seeds for LFSR-Based Test Generation From Non test Cubes - 2016
  • Design and Implementation of Digital low power base band processor for RFID Tags (2010)
  • Low-Cost High-Performance VLSI Architecture forMontgomery Modular Multiplication - 2016
  • Glitch free combinational clock gating approach in nanometer VLSI circuits - 2015
  • Performance Analysis of a Low-Power High-Speed Hybrid 1-bit Full Adder Circuit - 2017
  • PNS-FCR: Flexible Charge RecyclingDynamic Circuit Technique forLow-Power Microprocessors - 2016
  • A Low Power Trainable Neuromorphic IntegratedCircuit That Is Tolerant to Device Mismatch - 2016
  • DLAU: A Scalable Deep Learning Accelerator Unit on FPGA - 2017
  • ROOT
  • Logic Gates
Previous article: Multiple Constant Multiplication Algorithmfor High-Speed and Low-Power Design - 2016 Multiple Constant Multiplication Algorithmfor High-Speed and Low-Power Design - 2016 Next article: Low-Power Parallel Chien Search ArchitectureUsing a Two-Step Approach - 2016 Low-Power Parallel Chien Search ArchitectureUsing a Two-Step Approach - 2016
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