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Hardware and software architectures ...

Cho, Inkeun.

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Hardware and software architectures for energy- and resource-efficient signal processing systems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Hardware and software architectures for energy- and resource-efficient signal processing systems./
作者:	Cho, Inkeun.
面頁冊數:	119 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-11(E), Section: B.
Contained By:	Dissertation Abstracts International75-11B(E).
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3628747
ISBN:	9781321051469

Hardware and software architectures for energy- and resource-efficient signal processing systems.
Cho, Inkeun.

Hardware and software architectures for energy- and resource-efficient signal processing systems. - 119 p.

Source: Dissertation Abstracts International, Volume: 75-11(E), Section: B.

Thesis (Ph.D.)--University of Maryland, College Park, 2014.

For a large class of digital signal processing (DSP) systems, design and implementation of hardware and software is challenging due to stringent constraints on energy and resource requirements. In this thesis, we develop methods to address this challenge by proposing new constraint-aware system design methods for DSP systems, and energy- and resource-optimized designs of key DSP subsystems that are relevant across various application areas. In addition to general methods for optimizing energy consumption and resource utilization, we present streamlined designs that are specialized to efficiently address platform-dependent constraints.

ISBN: 9781321051469Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Hardware and software architectures for energy- and resource-efficient signal processing systems.
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245 1 0 $a Hardware and software architectures for energy- and resource-efficient signal processing systems.
300 $a 119 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-11(E), Section: B.
500 $a Adviser: Shuvra S. Bhattacharyya.
502 $a Thesis (Ph.D.)--University of Maryland, College Park, 2014.
520 $a For a large class of digital signal processing (DSP) systems, design and implementation of hardware and software is challenging due to stringent constraints on energy and resource requirements. In this thesis, we develop methods to address this challenge by proposing new constraint-aware system design methods for DSP systems, and energy- and resource-optimized designs of key DSP subsystems that are relevant across various application areas. In addition to general methods for optimizing energy consumption and resource utilization, we present streamlined designs that are specialized to efficiently address platform-dependent constraints.
520 $a We focus on two specific aspects in development of energy- and resource-optimized design techniques: (1) Application-specific systems and architectures for energy- and resource- efficient design..
520 $a First, we address challenges in efficient implementation of wireless sensor network building energy monitoring systems (WSNBEMSs). We develop new energy management schemes in order to maximize system lifetime for WSNBEMSs, and demonstrate that system lifetime can be improved significantly without affecting monitoring accuracy.
520 $a We also present resource efficient, field programmable gate array (FPGA) architecture for implementation of orthogonal frequency division multiplexing (OFDM) systems. We have demonstrated that our design provides at least 8.8% enhancement in terms of resource efficiency compared to Xilinx FFT v7.1 within the same OFDM configuration. (2) Dataflow-based methods for structured design and implementation of energy- and resource- efficient DSP systems. .
520 $a First, we introduce a dataflow-based design approach based on integrating interrupt-based signal acquisition in context of parameterized synchronous dataflow (PSDF) modeling. We demonstrate that by applying our approach, energy- and resource-efficient embedded software can be derived systematically from high level models of dynamic, data-driven applications systems (DDDASs) functional structure.
520 $a Also, we present an in-depth development of lightweight dataflow-Verilog (LWDF-V), which is an integration of the LWDF programming model with the Verilog hardware description language (HDL), and we demonstrate the utility of LWDF-V for design and implementation of digital systems for signal processing. We emphasize efficient of LWDF with HDLs, and emphasize the application of LWDF-V to design DSP systems with dynamic parameters on FPGA platforms.
590 $a School code: 0117.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Computer Science. $3 626642
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710 2 $a University of Maryland, College Park. $b Electrical Engineering. $3 1018746
773 0 $t Dissertation Abstracts International $g 75-11B(E).
790 $a 0117
791 $a Ph.D.
792 $a 2014
793 $a English
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