For multiple signal-processing applications, estimating the target's speed, distance, and elevation angle by using applications running in real time and consequently, fast data rates is important. Custom hardwares...
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For multiple signal-processing applications, estimating the target's speed, distance, and elevation angle by using applications running in real time and consequently, fast data rates is important. Custom hardwares, such as field programmable gate arrays (FPGAs), are often used to prototype and deploy such signal-processing algorithms. Multiple signal classification (MUSIC) is typically used for direction-of-arrival (DOA) estimation. It involves complex mathematical operations such as covariance matrix computation, eigen value decomposition, and peak value search for signal values. With a novel high-level synthesis (HLS)-based design approach that optimizes the bit widths for the eigen value decomposition logic, this study presents an area and speed-optimal implementation of MUSIC algorithm on FPGA. The final implementation involving the covariance matrix computation, eigen value decomposition, and peak search was implemented on Xilinx Zynq (XC7Z020) FPGA. Because of its optimum bit widths, area utilization was minimized and operation frequency on the target FPGA was maximized. The proposed design works in real time to estimate the DOA in less than 1.7 mu s (15 % faster than reported values) and uses up to 30 % less resources on the target FPGA compared with other reported implementations.
Physiological and clinical and translation tools, the wearable device of semiconductor technology equipped with the convergence prediction of health analysis to advanced sports. Test and physical performance, physiolo...
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Physiological and clinical and translation tools, the wearable device of semiconductor technology equipped with the convergence prediction of health analysis to advanced sports. Test and physical performance, physiological condition, biochemical composition, and subsequent application of indicators associated with mental warning players, development plans, as indicated by the physician or training teams, surrounding player?s performance, improve the protocol?s agreement, reduce the risk of injury. Provide an understanding of sports medicine wearable sensors. Commercial devices will include those described in the scientific literature. The primary purpose is to provide wearable technology to assess the biomechanical and physiological parameters of athletes. The second purpose of, the usefulness of this technology is, to a certain extent, it?s streaming players in various sports fields between the performances of the joint research, academic research groups, sports medicine clinic, and sports teams. It is to identify opportunities. Companion, the wisdom of monitoring biochemical indicators and the player of the wearable use.
This work presents a design framework for real-time image and video processing enabling exploration and evaluation of different processing techniques. The goal of our educational approach is to develop a flexible and ...
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This work presents a design framework for real-time image and video processing enabling exploration and evaluation of different processing techniques. The goal of our educational approach is to develop a flexible and easily customizable environment for prototyping different processing techniques on field programmable gate arrays (FPGAs), targeting specific applications. In this paper we give an overview of different requirements and techniques of video processing featuring FPGAs. Three real-time video processing algorithms were combined to show the advantages and characteristics of our approach. Within the framework, the modules running in parallel can be easily swapped at run-time according to the application specific needs.
This paper presents a high throughput hardware architecture for deblocking filter in high efficiency video coding (H.265/HEVC) standard. The architecture uses an efficient hybrid pipelining and parallel processing tec...
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This paper presents a high throughput hardware architecture for deblocking filter in high efficiency video coding (H.265/HEVC) standard. The architecture uses an efficient hybrid pipelining and parallel processing techniques for intra encoder. A single edge filter is designed to process both horizontal and vertical filtering of pixels one after the other respectively. In our proposed architecture, the video frame is divided into 32 x 32 blocks and each block is processed by splitting them into blocks of 8 x 32 pixels in a pipelined manner. Parallel processing is employed for filtering the edges which helped in improving the throughput by decreasing the processing clock cycles. It has been observed that the largest coding tree unit block that the hardware architecture can process is 64 x 64 pixels and can be achieved in 64 clock cycles. Synthesis results of the Verilog design for the proposed architecture using application specific integrated circuit 180 nm standard cell library shows that it consumes 102k 2-input NAND gates and can work at a maximum clock frequency of 250 MHz. The proposed design is capable of supporting 8k ultra high definition video sequences at 322 Frames Per Second (fps) which is the best among the existing present-day architectures.
This paper presents a real-time hybrid simulation (RTHS) strategy where the numerical and experimental substructures are executed at two different rates to optimize computational resources while maintaining an effecti...
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This paper presents a real-time hybrid simulation (RTHS) strategy where the numerical and experimental substructures are executed at two different rates to optimize computational resources while maintaining an effective actuator control. The concept is referred to here as multi-rate real-time hybrid simulation (mrRTHS), and this approach is intended to enable low-cost RTHS by facilitating testing in the case of limited computational resources. Operated on a Laboratory Virtual Engineering Workshop (LabVIEW) real-time target, the mrRTHS concept is demonstrated through both a single- and multipledegree-of-freedom (SDOF) and (MDOF) mass-springdamper system. The numerical substructure generates a displacement signal with a coarse time step of Delta t. Using the current and three previous displacement data points, a finer control signal is defined with a time step of delta t, using a third-order polynomial algorithm referred to here as the polynomial fitting extrapolator. Both the numerical substructure and polynomial fitting extrapolator is executed with a sampling rate of Delta t by an on-board single-core processor-referred to here as the digital signal processor (DSP). Through a field-programmablegatearray (FPGA) the control signal is compensated and transmitted to the transfer system through an I/O module with a sampling rate of 1 kHz (i.e. delta t = 0.001 sec). The ratio between Delta t and delta t are an integer-referred to here as the execution ratio. For an execution ratio of 1:5 and 1:10 the system performance is evaluated against a numerical model of the emulated structure-referred to here as the reference structure. For both the SDOF and MDOF system, a good correlation between the mrRTHS and reference is achieved with execution ratios of 1:5 and 1:10. When changing the execution ratio from 1:5 to 1:10, approximately 50% reduction of the required computational resources on the DSP is achieved.
We develop a custom hardware architecture for real-time implementation of embedded Model Predictive Control (MPC) on a field programmable gate array (FPGA). We propose a novel modular framework that allows for easy an...
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We develop a custom hardware architecture for real-time implementation of embedded Model Predictive Control (MPC) on a field programmable gate array (FPGA). We propose a novel modular framework that allows for easy and rapid prototyping of control with capability for analog-to-digital conversion, numerical scaling, and digital-to-analog conversion. We demonstrate the effectiveness of the proposed framework for real-time control on a quadruple water tank system.
The application of FPGAs (field programmable gate array) became an important issue in designing electronic systems. Also, the flexibility and performance offered by reconfigurable computing shorts the development time...
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The application of FPGAs (field programmable gate array) became an important issue in designing electronic systems. Also, the flexibility and performance offered by reconfigurable computing shorts the development time required for implementing digital signal processing solutions using FPGAs. In this paper, we present original hardware designs of the BPSK and QPSK systems, using Matlab/Simulink environment, System Generator and Xilinx ISE, in order to verify the functionality of the systems in hardware which speeds up the simulations. The capabilities of the Spartan 3E board are also compared with previous reported results.
This article uses the subway traction power supply model as a simulation model to study the efficient and accurate real-time simulation of power systems with limited computing resources and real-time constraints. It f...
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This article uses the subway traction power supply model as a simulation model to study the efficient and accurate real-time simulation of power systems with limited computing resources and real-time constraints. It focuses on the resource optimization configuration method for multi-hardware real-time simulators. Firstly, the article distinguishes the tasks suitable for different hardware based on their different computing characteristics, the generality of CPU, and the inherent high parallelism and stronger computing capabilities of FPGA. Then, it adopts a physics-decoupled method to perform fine-grained partitioning of the resource occupation rate required for processing tasks on each hardware, so that each module can operate with the minimum resource occupation rate on the hardware, maximizing hardware resource savings and computational *** multi-level parallel real-time simulation architecture is formed through the coordination allocation of the coarse-grained and fine-grained partitioned model on the hardware, from hardware level, module level, to element level.
An Application Specific Inflexible FPGA (ASIF) is a tailored design, for a given group of known circuits, which is generated by extensively reducing the routing resources of an FPGA. In an ASIF, different dynamically ...
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An Application Specific Inflexible FPGA (ASIF) is a tailored design, for a given group of known circuits, which is generated by extensively reducing the routing resources of an FPGA. In an ASIF, different dynamically reconfigurable application circuits are initially mapped and tested on an FPGA fabric. Subsequently, the FPGA fabric is reduced to achieve an efficient architecture for known application circuits. However, a large portion of ASIF is still occupied by fully flexible logic blocks, containing the same amount of area and SRAM memory cells, as found in a traditional FPGA. Thus, here lies a potential to further optimize the logic blocks of an ASIF at the expense of removing or reducing their reconfigurability. This work optimizes the logic blocks of an ASIF through the SRAM-Table sharing technique, without compromising their reconfigurability. Moreover, the routing channels of ASIF are further optimized by applying the Boolean functions (gates) insertion technique. The applied techniques (SRAM-Table sharing and Boolean functions insertion) not only reduce the area, delay and power, but also minimize the reconfiguration time, bitstream size and the size of external memory required to store the bitstream of circuits. This optimized version of ASIF is termed as ASIF++. Furthermore, an embedded FPGA in a System-on-Chip that requires the partial dynamic reconfiguration for known circuits, can be automatically reduced to an ASIF++. It is found through experimental results that an ASIF++ is 4-9% area-efficient and requires 36% lesser number of SRAM cells, as compared to the previously proposed ASIF for a group of 2-5 circuits. It also achieves 34-53% area saving as compared to a traditional FPGA.
The synchronization of chaotic systems plays an extremely imperative and fundamental role in the fields of science and engineering. Notably, various external noise disturbances have a great impact on the synchronizati...
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The synchronization of chaotic systems plays an extremely imperative and fundamental role in the fields of science and engineering. Notably, various external noise disturbances have a great impact on the synchronization of chaotic systems because chaotic systems are quite sensitive to the change of their initial values. Consequently, the robustness of chaotic system synchronization must be considered in practical applications. From this viewpoint, the present paper proposes a disturbance suppression zeroing neural network (DSZNN) for robust synchronization of chaotic and hyperchaotic systems, and the DSZNN is implemented on field programmable gate array (FPGA) for further hardware validation. The distinctive features of the proposed DSZNN controller have the ability to suppress disturbance with faster convergent speed and higher accuracy compared with super-exponential zeroing neural network (SEZNN) and conventional zeroing neural network (CZNN). Moreover, theoretical analysis, comparative numerical simulations and hardware validations for the synchronization of a hyperchaotic system are presented to demonstrate the superior performance of the proposed DSZNN.
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