This paper introduces a coarse-grained FPGA architecture that is specialized for high-performance Finite Impulse Response (FIR) filtering. The proposed architecture provides the flexibility of a DSP processor with per...
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ISBN:
(纸本)9780897919784
This paper introduces a coarse-grained FPGA architecture that is specialized for high-performance Finite Impulse Response (FIR) filtering. The proposed architecture provides the flexibility of a DSP processor with performance and area efficiency similar to that of a custom ASIC design, while allowing all of the basic FIR design parameters, including coefficient precision, to be configured. Previous research has already shown that FPGAs can provide a high-performance alternative to DSP processors. Experimental comparisons in this paper show that the performance and area efficiency of the proposed architecture is similar to that of custom approaches across a wide range of filter sizes and configurations.
Synthetic aperture (SA) imaging techniques have drawn many attentions since they are capable of providing improved spatial resolution over conventional receive dynamic focusing (CRDF) methods. However, the processing ...
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ISBN:
(纸本)9781457703829
Synthetic aperture (SA) imaging techniques have drawn many attentions since they are capable of providing improved spatial resolution over conventional receive dynamic focusing (CRDF) methods. However, the processing of SA imaging is computationally demanding for real-time processing. Furthermore, massive memories for storing the pre-beamformed radio frequency (RF) data are required, leading to substantial increase in hardware complexity. In this paper, we propose the efficient real-time SA beamformer architecture that could be integrated in modern ultrasound imaging systems. The feasibility of the proposed architecture was demonstrated by implementing a 64-channel SA beamformer on two high-performance field programmable gate arrays (FPGAs, Virtex-5 SX95T, Xilinx, USA). The developed SA beamformer can support up to 12 synthesis beams by utilizing 61percent of slice registers, 43percent of lookup tables (LUTs), 89percent of random access memories (RAMs) and 51percent of digital signal processing (DSP) blocks in each FPGA.
The paper focuses on a wireless myoelectric prosthesis of the upper-limb that uses a Multilayer Perceptron(MLP) neural network with back propagation algorithm in classifying electromyography(EMG) *** Neural network is...
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The paper focuses on a wireless myoelectric prosthesis of the upper-limb that uses a Multilayer Perceptron(MLP) neural network with back propagation algorithm in classifying electromyography(EMG) *** Neural network is composed of processing units that have the capability of sending signals to each other and perform a desired *** algorithm is widely used in pattern *** network is used to train EMG signals and use it in performing the necessary hand positions of the *** programming a field programmable gate array(FPGA) using Verilog and transmission of data with Zigbee,the EMG signals are acquired,classified,and simulated *** signals are classified and trained to produce the necessary hand *** corresponding hand movements of Open,Pick,Hold and Grip are simulated through the Zigbee controller.Z-test is used to analyze the data that were produced and acquired from using the neural network.
As FPGA capacity increases, a growing challenge is connecting ever-more components with the current low-level FPGA interconnect while keeping designers productive and on-chip communication efficient. We propose augmen...
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As FPGA capacity increases, a growing challenge is connecting ever-more components with the current low-level FPGA interconnect while keeping designers productive and on-chip communication efficient. We propose augmenting FPGAs with networks-on-chip (NoCs) to simplify design, and we show that this can be done while maintaining or even improving silicon efficiency. We compare the area and speed efficiency of each NoC component when implemented hard versus soft to explore the space and inform our design choices. We then build on this component-level analysis to architect hard NoCs and integrate them into the FPGA fabric;these NoCs are on average 20-23x smaller and 5-6x faster than soft NoCs. A 64-node hard NoC uses only similar to 2% of an FPGA's silicon area and metallization. We introduce a new-communication efficiency metric: silicon area required per realized communication bandwidth. Soft NoCs consume 4960 mm(2)/TBps, but hard NoCs are 84x more efficient at 59 mm(2)/TBps. Informed design can further reduce the area overhead of NoCs to 23 mm(2)/TBps, which is only 2.6x less efficient than the simplest point-to-point soft links (9 mm(2)/TBps). Despite this almost comparable efficiency, NoCs can switch data across the entire FPGA while point-to-point links are very limited in capability;therefore, hard NoCs are expected to improve FPGA efficiency for more complex styles of communication.
This paper proposes a system-on-chip (SoC) FPGA - based real-time video processing platform for background and foreground identification. Background and foreground identification is a co mmon feature in many tasks in ...
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ISBN:
(纸本)9781479953424
This paper proposes a system-on-chip (SoC) FPGA - based real-time video processing platform for background and foreground identification. Background and foreground identification is a co mmon feature in many tasks in video content analytics (VCA), including object detection, tracking, segmentation and recognition. VCA is a relatively new field in video processing;it has generally been implemented using two chips, with the image signal processing (ISP) part in a DSP or an FPGA and the VCA part executed by a processor. However, a new generation of SoC FPGAs that incorporates a processor and an FPGA into a single chip makes it possible for a single chip to perform both ISP and VCA. This study details the hardware implementation of a real-time background and foreground identification algorithm in an SoC, including the capture, processing and display stages. The proposed platform uses photometric invariant color, depth data and local binary patterns (LBPs) to distinguish backgrounds from foregrounds. The system uses minimal cell resources and tries to implement modules using a pipeline technique.
This paper presents a signal processing methodology to analyze Electrocardiography(ECG) signals. Discrete Wavelet Transform(DWT) is used as a feature extraction methodology to achieve efficient design. Baseline wander...
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This paper presents a signal processing methodology to analyze Electrocardiography(ECG) signals. Discrete Wavelet Transform(DWT) is used as a feature extraction methodology to achieve efficient design. Baseline wandering noise is removed in this design using Lest-Square Linear Phase FIR methodology. ECG signals classification is done using Feed forward neural network methodology. An accuracy of 100% in identifying the normal samples, and accuracy of 95.23% for identifying abnormal ECG beats are obtained, achieving a total accuracy of 97.78% for identifying ECG signals using this presented methodology.
The main advantage of cerebellar model articulation controller (CMAC) is its fast learning rate compared to other neural networks since it can provide more potential to enrich the mapping relationship between inputs a...
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The main advantage of cerebellar model articulation controller (CMAC) is its fast learning rate compared to other neural networks since it can provide more potential to enrich the mapping relationship between inputs and outputs. This paper proposes a robust adaptive CMAC system for brushless DC motors with PI type parameter adaptation. CMAC is used to mimic an ideal controller based on the Lyapunov stability theory, and the robust controller is designed to achieve L{sub}2 tracking performance with desired attenuation level. The robust adaptive CMAC system is implemented on a field programmable gate array chip and is applied to brushless DC (BLDC) motor control. Some experimental results verify that the proposed robust adaptive CMAC method can achieve good parameter adaptation and favorable tracking performance.
The control performance of converter directly affects the drive efficiency of electric vehicle(EV).This paper studies on the model predictive control(MPC) based controller design of battery integrated modular mult...
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The control performance of converter directly affects the drive efficiency of electric vehicle(EV).This paper studies on the model predictive control(MPC) based controller design of battery integrated modular multilevel converter(B-MMC).Aiming at the goal of three-phase current tracking and battery balancing control of B-MMC,three-layer controllers are *** first controller is the finite control set model predictive control(FCS-MPC),which realizes the motor drive by tracking the phase *** second controller is the circulation controller for the active balance control of *** is composed of multiple proportional controllers to realize the battery balance between the bridge *** third controller is the battery sorting algorithm to achieve the passive balance control of the battery in the same bridge *** the same time,field programmable gate array(FPGA) is used to accelerate the controller to meet the real-time requirements of ***,the simulation results of the B-MMC control system validates the effectiveness of the control algorithm.
The optical ZCZ code is a set of pairs of binary and bi-phase sequences with zero correlation zone. An optical code division multiple access (CDMA) system using this code can remove co-channel interference and influen...
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The optical ZCZ code is a set of pairs of binary and bi-phase sequences with zero correlation zone. An optical code division multiple access (CDMA) system using this code can remove co-channel interference and influence of multi-path. We proposed the compact construction of a bank of matched filters for this code in a receiver. But we have not proposed the construction of a code generator for this code in a transmitter yet.
In this paper, we propose the construction of two code generators for an optical ZCZ code using a Sylvester-type Hadamard matrix, which are called ROM-type and non ROM- type code generators. This ROM-type code generator can be constructed by a ROM and a up-counter. Similarly,this non ROM-type code generator can be constructed by a up-counter, flip-flops and logic gates. The ROM-type and non ROM-type code generators are implemented on a field programmable gate array (FPGA) corresponding to 400,000 logic gates, and the non ROM-type code generator can reduce logic elements than the ROM-type code generator.
This paper presents the TURTLE fault injection platform for inserting faults into SRAM FPGAs. The TURTLE system is designed to gather significant fault injection data to test and validate radiation-induced single-even...
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ISBN:
(纸本)9781728119588
This paper presents the TURTLE fault injection platform for inserting faults into SRAM FPGAs. The TURTLE system is designed to gather significant fault injection data to test and validate radiation-induced single-event upset (SEU) mitigation techniques for FPGAs. The TURTLE is a low-cost fault injection platform that emulates upsets within the configuration memory (CRAM) of an FPGA through partial reconfiguration. This work successfully implemented the proposed architecture and performed several successful fault injection campaigns on multiple designs and SEU mitigation techniques. Results in this paper show large amounts of data collected from a fault injection campaign used to validate the PCMF SEU mitigation technique. Over 170 million injections were performed using the TURTLE for this campaign.
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