• Title/Summary/Keyword: hardware implementation

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A Study on Hardware Implementation of a VSB Equalization System (VSB 등화시스템의 하드웨어 구현방법에 관한 연구)

  • 채승수;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.10
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    • pp.1314-1325
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    • 1995
  • In this paper, we describe hardware implementation of VSB (Vestigial SideBand) mo-dulation equalization systems for HDTV (High Definition TeleVision). By modifying an adaptive equalization algorithm, we propose a hardware architecture with a low hardware cost and the performance close to floating-point operations. We also employ the pipeline concept to reduce the hardware cost. The effectiveness of the proposed hardware architecture is de- monstrated through computer simulation and the optimization result of VHDL circuit descriptions.

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Hardware Implementation of Time Skew Calibration Block for Time Interleaved ADC (TI ADC를 위한 시간 왜곡 교정 블록의 하드웨어 구현)

  • Khan, Sadeque Reza;Choi, Goangseog
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.3
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    • pp.35-42
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    • 2017
  • This paper presents hardware implementation of background timing-skew calibration technique for time-interleaved analog-to-digital converters (TI ADCs). The timing skew between any two adjacent analog-digital (A/D) channels is detected by using pure digital Finite Impulse Response (FIR) delay filter. This paper includes hardware architecture of the system, main units and small sub-blocks along with control logic circuits. Moreover, timing diagrams of logic simulations using ModelSim are provided and discussed for further understanding about simulations. Simulation process in MATLAB and Verilog is also included and provided with basic settings need to be done. For hardware implementation it not practical to work with all samples. Hence, the simulation is conducted on 512 TI ADC output samples which are stored in the buffer simultaneously and the correction arithmetic is done on those samples according to the time skew algorithm. Through the simulated results, we verified the implemented hardware is working well.

A Hardware Implementation of Simple Genetic Algorithm for Evolvable System (진화적응을 위한 유전알고리즘의 하드웨어 구현)

  • Dong, Sung-Soo
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.463-464
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    • 2007
  • This paper presents the hardware-based genetic algorithm, written in VHDL. Due to parallel computation and no function call overhead, a hardware-based GA advantage a speedup over a software-based GA. The proposed architecture is constructed on a field-programmable gate arrays, which are easily reconfigured. Since a general-purpose GA requires that the fitness function be easily changed, the hardware implementation must exploit the reprogrammability.

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Embedded One Chip Computer Design for Hardware Implementation of Genetic Algorithm (유전자 알고리즘 하드웨어 구현을 위한 전용 원칩 컴퓨터의 설계)

  • 박세현;이언학
    • Journal of Korea Multimedia Society
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    • v.4 no.1
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    • pp.82-90
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    • 2001
  • Genetic Algorithm(GA) has known as a method of solving NP problem in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementation of Genetic Algorithm is focused on in recent studies. This paper proposes a new type of embedded one chip computer fort Hardware Implementation of Genetic Algorithm. The proposed embedded one chip computer consists of 16 Bit CPU care and hardware of genetic algorithm. In contrast to conventional hardware oriented GA which is dependent on main computer in the process of GA, the proposed embedded one chip computer is independent on main computer. Conventional hardware GA uses the fixed length of chromosome but the proposed embedded one chip computer uses the variable length of chromosome by employing the efficient 16 bit Pipeline Unit. Experimental results show that the proposed one chip computer is applicable to the design of evolvable hardware for Random NRZ bit synchronization circuit.

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A novel hardware design for SIFT generation with reduced memory requirement

  • Kim, Eung Sup;Lee, Hyuk-Jae
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.13 no.2
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    • pp.157-169
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    • 2013
  • Scale Invariant Feature Transform (SIFT) generates image features widely used to match objects in different images. Previous work on hardware-based SIFT implementation requires excessive internal memory and hardware logic [1]. In this paper, a new hardware organization is proposed to implement SIFT with less memory and hardware cost than the previous work. To this end, a parallel Gaussian filter bank is adopted to eliminate the buffers that store intermediate results because parallel operations allow all intermediate results available at the same time. Furthermore, the processing order is changed from the raster-scan order to the block-by-block order so that the line buffer size storing the source image is also reduced. These techniques trade the reduction of memory size with a slight increase of the execution time and external memory bandwidth. As a result, the memory size is reduced by 94.4%. The proposed hardware for SIFT implementation includes the Descriptor generation block, which is omitted in the previous work [1]. The addition of the hardwired descriptor generation improves the computation speed by about 30 times when compared with the previous work.

Hardware Implementation of Genetic Algorithm for Evolvable Hardware (진화하드웨어 구현을 위한 유전알고리즘 설계)

  • Dong, Sung-Soo;Lee, Chong-Ho
    • 전자공학회논문지 IE
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    • v.45 no.4
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    • pp.27-32
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    • 2008
  • This paper presents the implementation of simple genetic algorithm using hardware description language for evolvable hardware embedded system. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results for several fitness functions.

Auto Exposure Algorithm And Hardware Implementation for application of Mobile Phone Camera (모바일 폰 카메라에 적용하기 위한 자동노출 알고리즘 개발 및 하드웨어 설계)

  • Kim, Kyung-Rin;Ha, Joo-Young;Kang, Bong-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.1
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    • pp.29-36
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    • 2009
  • In this paper, we proposed auto exposure(AE) algorithm and hardware implementation for apply to mobile phone camera. AE is a function that control camera exposure automatically for appropriate to object. Existing AE is using micro controller unit and there are some problems about high expense and slow processing speed. For improve these problems, we proposed AE algorithm for hardware implementation without micro controller unit therefor we can expect improvement about the content of a production and operation speed. We proposed the algorithm that is considered efficiency of hardware resource and the results of hardware implementation of proposed AE algorithm apply to mobile phone camera sensor, we verified proposed AE function.

Implementation of FPGA for Efficient Ray Tracing Hardware Supporting Dynamic Scenes (동적 장면을 지원하는 효율적인 광선 추적 하드웨어에 대한 FPGA상에서의 구현)

  • Lee, Jin Young;Kim, Cheong Ghil;Park, Woo-Chan
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.4
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    • pp.23-26
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    • 2022
  • In this paper, our ray tracing hardware is implemented on the latest high-capacity FPGA board. The system included ray tracing hardware for rendering and tree building hardware for handling dynamic scenes. The FPGA board used in the implementation is a Xilinx Alveo U250 accelerator card for data centers. This included 12 ray tracing hardware cores and 1 tree-building hardware core. As a result of testing in various scenes in Full HD resolution, the FPS performance of the proposed ray tracing system was measured from 8 to 28. The overall average is about 17.7 FPS.

Hardware Implementation of Genetic Algorithm and Its Analysis (유전알고리즘의 하드웨어 구현 및 실험과 분석)

  • Dong, Sung-Soo;Lee, Chong-Ho
    • 전자공학회논문지 IE
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    • v.46 no.2
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    • pp.7-10
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    • 2009
  • This paper presents the implementation of libraries of hardware modules for genetic algorithm using VHDL. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results and analysis for several fitness functions. It can be seen that our design works well for the three examples.

Microstep Stepper Motor Control Based on FPGA Hardware Implementation

  • Chivapreecha, Sorawat;Dejhan, Kobchai
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.93-97
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    • 2005
  • This paper proposes a design of stepper motor control in microstep driven mode using FPGA (Field Programmable Gate Array) for hardware implementation. The methods to drive stepper motor in microstep excitation mode are to control of the controlling currents in each phase windings of stepper motor with reference signals. These reference signals are used for controlling the current levels, the required variation of current levels with rotor position can be obtained from the ideal linear or sinusoidal approximations to the static torque-displacement ($T-{\theta}$) characteristic curve. In addition, the hardware implementation of stepper motor controller can be designed uses VHDL (Very high speed integrated circuits Hardware Description Language) and synthesis using an Altera FPGA, FLEX10K family, EPF10K20RC240-4 device as target technology and use MAX+PlusII program for overall development. A multi-stack variable-reluctance stepper motor of Sanyo Denki is used in the experiments.

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