In order to obtain variable characteristics,the digital filter's type,number of taps and coefficients should be changed constantly such that the desired frequency-domain characteristics can be obtained.This paper ...In order to obtain variable characteristics,the digital filter's type,number of taps and coefficients should be changed constantly such that the desired frequency-domain characteristics can be obtained.This paper proposes a method for self-programmable variable digital filter(VDF) design based on field programmable gate array(FPGA).We implement a digital filter system by using custom embedded micro-processor,programmable finite impulse response(P-FIR) macro module,coefficient-loader,clock manager and analog/digital(A/D) or digital/analog(D/A) controller and other modules.The self-programmable VDF can provide the best solution for realization of digital filter algorithms,which are the low-pass,high-pass,band-pass and band-stop filter algorithms with variable frequency domain characteristics.The design examples with minimum 1 to maximum 32 taps FIR filter,based on Modelsim post-routed simulation and onboard running on XUPV5-LX110T,are provided to demonstrate the effectiveness of the proposed method.展开更多
An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the conv...An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the converter was mapped into a look-up table that was synthesized into a set of Boolean equations. A VLSI chip–a field programmable gate array (FPGA) was used to implement the Boolean equations. Features include the size of RAM chip independent of number of rules in the knowledge base, on-chip fuzzification and defuzzification, faster response with speeds over giga fuzzy logic inferences per sec (FLIPS), and an inexpensive VLSI chip. The key application areas are: 1) on-chip integrated controllers;and 2) on-chip co-integration for entire system of sensors, circuits, controllers, and detectors for building complete instrument systems.展开更多
Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for...Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.展开更多
As a core component in intelligent edge computing,deep neural networks(DNNs)will increasingly play a critically important role in addressing the intelligence-related issues in the industry domain,like smart factories ...As a core component in intelligent edge computing,deep neural networks(DNNs)will increasingly play a critically important role in addressing the intelligence-related issues in the industry domain,like smart factories and autonomous driving.Due to the requirement for a large amount of storage space and computing resources,DNNs are unfavorable for resource-constrained edge computing devices,especially for mobile terminals with scarce energy supply.Binarization of DNN has become a promising technology to achieve a high performance with low resource consumption in edge computing.Field-programmable gate array(FPGA)-based acceleration can further improve the computation efficiency to several times higher compared with the central processing unit(CPU)and graphics processing unit(GPU).This paper gives a brief overview of binary neural networks(BNNs)and the corresponding hardware accelerator designs on edge computing environments,and analyzes some significant studies in detail.The performances of some methods are evaluated through the experiment results,and the latest binarization technologies and hardware acceleration methods are tracked.We first give the background of designing BNNs and present the typical types of BNNs.The FPGA implementation technologies of BNNs are then reviewed.Detailed comparison with experimental evaluation on typical BNNs and their FPGA implementation is further conducted.Finally,certain interesting directions are also illustrated as future work.展开更多
In order to solve the current high failure rate of warship equipment field programmable gate array( FPGA) software,fault detection is not timely enough and FPGA detection equipment is expensive and so on. After in-dep...In order to solve the current high failure rate of warship equipment field programmable gate array( FPGA) software,fault detection is not timely enough and FPGA detection equipment is expensive and so on. After in-depth research,this paper proposes a warship equipment FPGA software based on Xilinx integrated development environment( ISE) and ModelSim software.Functional simulation and timing simulation to verify the correctness of the logic design of the FPGA,this method is very convenient to view the signal waveform inside the FPGA program to help FPGA test engineers to achieve FPGA fault prediction and diagnosis. This test method has important engineering significance for the upgrading of warship equipment.展开更多
The intellectual property (IP) core for inter-integrated circuit (IIC) bus controller is designed using finite state machine (FSM) based on field programmable gate array (FPGA). Not only the data from AT 24C02...The intellectual property (IP) core for inter-integrated circuit (IIC) bus controller is designed using finite state machine (FSM) based on field programmable gate array (FPGA). Not only the data from AT 24C02C can be read automatically after power on, but also the data from upper computer can be written into AT24C02C immediately under the control of the IIC bus controller. When it is applied to blast wave overpressure test system, the IIC bus controller can read and store working parameters automatically. In a laboratory environment, the IP core simulation is carried out and the result is accurate. In the explosion field test, by analyzing the obtained valid data, it can be concluded that the designed IP core has good reliability.展开更多
The design of an FPGA( field programmable gate array) based programmable SONET (synchronous optical network) OC-192 10 Gbit/s PRBS (pseudo-random binary sequence) generator and a bit interleaved polarity 8 (BI...The design of an FPGA( field programmable gate array) based programmable SONET (synchronous optical network) OC-192 10 Gbit/s PRBS (pseudo-random binary sequence) generator and a bit interleaved polarity 8 (BIP-8) error detector is presented. Implemented in a parallel feedback configuration, this tester features PRBS generation of sequences with bit lengths of 2^7 - 1,2^10- 1,2^15 - 1,2^23 - land 2^31 - 1 for up to 10 Gbit/s applications with a 10 Gbit/s optical transceiver, via the SFI-4 (OC-192 serdes-framer interface). In the OC-192 frame alignment circuit, a dichotomy search algorithm logic which performs the functions of word alignment and STM-64/OC192 de-frame speeds up the frame sync logic and reduces circuit complexity greatly. The system can be used as a low cost tester to evaluate the performance of OC-192 devices and components, taking the replacement of precious commercial PRBS testers.展开更多
To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network(ANN) hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta(Σ...To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network(ANN) hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta(ΣΔ) modulation is presented.The bit-stream adder,multiplier,threshold function unit and fully digital ΣΔ modulator are implemented in a field programmable gate array(FPGA),and these bit-stream arithmetical units are employed to build the bit-stream artificial neuron.The function of the bit-stream artificial neuron is verified through the realization of the logic function and a linear classifier.The bit-stream perceptron based on the bit-stream artificial neuron with the pre-processed structure is proved to have the ability of nonlinear classification.The FPGA resource utilization of the bit-stream artificial neuron shows that the bit-stream ANN hardware implementation method can significantly reduce the demand of the ANN hardware resources.展开更多
Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we p...Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control.We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians.Additionally,we present an efficient,grid-free numerical solver based on our representation formulas,which is shown to scale linearly with the state dimension,and thus,to overcome the curse of dimensionality.Using existing optimization methods and the min-plus technique,we extend our numerical solvers to address more general classes of convex and nonconvex initial costs.We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit(CPU)and a field-programmable gate array(FPGA).In several cases,our FPGA implementation obtains over a 10 times speedup compared to the CPU,which demonstrates the promising performance boosts FPGAs can achieve.Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.展开更多
Because single line-scan camera loses light in the edge of the sensor when the field of view is large, a mosaic cam- era based on field programmable gate array (FPGA) is presented by putting multiple cameras arrange...Because single line-scan camera loses light in the edge of the sensor when the field of view is large, a mosaic cam- era based on field programmable gate array (FPGA) is presented by putting multiple cameras arranged in a straight line to share the field of view and reduce the view angle of every camera. For detecting doping micro particles with the designed mosaic line-scan camera, a detection algorithm of the target's location in FPGA is proposed. Finally, the practicability and stability of the system were validated experimentally. The results of the experiment show that the camera can get images clearly with less light loss and can accurately distinguish the target and the background.展开更多
基金Science &Technology Plan Foundation of Hunan Province,China(No.2010F3102)Science Research Foundation of Hunan Province,China(No.08C392)
文摘In order to obtain variable characteristics,the digital filter's type,number of taps and coefficients should be changed constantly such that the desired frequency-domain characteristics can be obtained.This paper proposes a method for self-programmable variable digital filter(VDF) design based on field programmable gate array(FPGA).We implement a digital filter system by using custom embedded micro-processor,programmable finite impulse response(P-FIR) macro module,coefficient-loader,clock manager and analog/digital(A/D) or digital/analog(D/A) controller and other modules.The self-programmable VDF can provide the best solution for realization of digital filter algorithms,which are the low-pass,high-pass,band-pass and band-stop filter algorithms with variable frequency domain characteristics.The design examples with minimum 1 to maximum 32 taps FIR filter,based on Modelsim post-routed simulation and onboard running on XUPV5-LX110T,are provided to demonstrate the effectiveness of the proposed method.
文摘An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the converter was mapped into a look-up table that was synthesized into a set of Boolean equations. A VLSI chip–a field programmable gate array (FPGA) was used to implement the Boolean equations. Features include the size of RAM chip independent of number of rules in the knowledge base, on-chip fuzzification and defuzzification, faster response with speeds over giga fuzzy logic inferences per sec (FLIPS), and an inexpensive VLSI chip. The key application areas are: 1) on-chip integrated controllers;and 2) on-chip co-integration for entire system of sensors, circuits, controllers, and detectors for building complete instrument systems.
基金financially supported by the National Council for Scientific and Technological Development(CNPq,Brazil),Swedish-Brazilian Research and Innovation Centre(CISB),and Saab AB under Grant No.CNPq:200053/2022-1the National Council for Scientific and Technological Development(CNPq,Brazil)under Grants No.CNPq:312924/2017-8 and No.CNPq:314660/2020-8.
文摘Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2022NSFSC0500the National Natural Science Foundation of China under Grant No.62072076.
文摘As a core component in intelligent edge computing,deep neural networks(DNNs)will increasingly play a critically important role in addressing the intelligence-related issues in the industry domain,like smart factories and autonomous driving.Due to the requirement for a large amount of storage space and computing resources,DNNs are unfavorable for resource-constrained edge computing devices,especially for mobile terminals with scarce energy supply.Binarization of DNN has become a promising technology to achieve a high performance with low resource consumption in edge computing.Field-programmable gate array(FPGA)-based acceleration can further improve the computation efficiency to several times higher compared with the central processing unit(CPU)and graphics processing unit(GPU).This paper gives a brief overview of binary neural networks(BNNs)and the corresponding hardware accelerator designs on edge computing environments,and analyzes some significant studies in detail.The performances of some methods are evaluated through the experiment results,and the latest binarization technologies and hardware acceleration methods are tracked.We first give the background of designing BNNs and present the typical types of BNNs.The FPGA implementation technologies of BNNs are then reviewed.Detailed comparison with experimental evaluation on typical BNNs and their FPGA implementation is further conducted.Finally,certain interesting directions are also illustrated as future work.
文摘In order to solve the current high failure rate of warship equipment field programmable gate array( FPGA) software,fault detection is not timely enough and FPGA detection equipment is expensive and so on. After in-depth research,this paper proposes a warship equipment FPGA software based on Xilinx integrated development environment( ISE) and ModelSim software.Functional simulation and timing simulation to verify the correctness of the logic design of the FPGA,this method is very convenient to view the signal waveform inside the FPGA program to help FPGA test engineers to achieve FPGA fault prediction and diagnosis. This test method has important engineering significance for the upgrading of warship equipment.
文摘The intellectual property (IP) core for inter-integrated circuit (IIC) bus controller is designed using finite state machine (FSM) based on field programmable gate array (FPGA). Not only the data from AT 24C02C can be read automatically after power on, but also the data from upper computer can be written into AT24C02C immediately under the control of the IIC bus controller. When it is applied to blast wave overpressure test system, the IIC bus controller can read and store working parameters automatically. In a laboratory environment, the IP core simulation is carried out and the result is accurate. In the explosion field test, by analyzing the obtained valid data, it can be concluded that the designed IP core has good reliability.
文摘The design of an FPGA( field programmable gate array) based programmable SONET (synchronous optical network) OC-192 10 Gbit/s PRBS (pseudo-random binary sequence) generator and a bit interleaved polarity 8 (BIP-8) error detector is presented. Implemented in a parallel feedback configuration, this tester features PRBS generation of sequences with bit lengths of 2^7 - 1,2^10- 1,2^15 - 1,2^23 - land 2^31 - 1 for up to 10 Gbit/s applications with a 10 Gbit/s optical transceiver, via the SFI-4 (OC-192 serdes-framer interface). In the OC-192 frame alignment circuit, a dichotomy search algorithm logic which performs the functions of word alignment and STM-64/OC192 de-frame speeds up the frame sync logic and reduces circuit complexity greatly. The system can be used as a low cost tester to evaluate the performance of OC-192 devices and components, taking the replacement of precious commercial PRBS testers.
基金The National Natural Science Foundation of China (No.60576028)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.11KJB510004)
文摘To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network(ANN) hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta(ΣΔ) modulation is presented.The bit-stream adder,multiplier,threshold function unit and fully digital ΣΔ modulator are implemented in a field programmable gate array(FPGA),and these bit-stream arithmetical units are employed to build the bit-stream artificial neuron.The function of the bit-stream artificial neuron is verified through the realization of the logic function and a linear classifier.The bit-stream perceptron based on the bit-stream artificial neuron with the pre-processed structure is proved to have the ability of nonlinear classification.The FPGA resource utilization of the bit-stream artificial neuron shows that the bit-stream ANN hardware implementation method can significantly reduce the demand of the ANN hardware resources.
基金supported by the DOE-MMICS SEA-CROGS DE-SC0023191 and the AFOSR MURI FA9550-20-1-0358supported by the SMART Scholarship,which is funded by the USD/R&E(The Under Secretary of Defense-Research and Engineering),National Defense Education Program(NDEP)/BA-1,Basic Research.
文摘Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control.We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians.Additionally,we present an efficient,grid-free numerical solver based on our representation formulas,which is shown to scale linearly with the state dimension,and thus,to overcome the curse of dimensionality.Using existing optimization methods and the min-plus technique,we extend our numerical solvers to address more general classes of convex and nonconvex initial costs.We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit(CPU)and a field-programmable gate array(FPGA).In several cases,our FPGA implementation obtains over a 10 times speedup compared to the CPU,which demonstrates the promising performance boosts FPGAs can achieve.Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.
基金National Natural Science Foundation of China(No.61227003,61171179,61302159)Natural Science Foundation of Shanxi Province(No.2012021011-2)+2 种基金Research Project Supported by Shanxi Scholarship Council of China(No.2013-083)Specialized Research Fund for the Doctoral Program of Higher Education,China(No.20121420110006)Top Science and Technology Innovation Teams of Higher Learning Institutions of Shanxi Province,China
文摘Because single line-scan camera loses light in the edge of the sensor when the field of view is large, a mosaic cam- era based on field programmable gate array (FPGA) is presented by putting multiple cameras arranged in a straight line to share the field of view and reduce the view angle of every camera. For detecting doping micro particles with the designed mosaic line-scan camera, a detection algorithm of the target's location in FPGA is proposed. Finally, the practicability and stability of the system were validated experimentally. The results of the experiment show that the camera can get images clearly with less light loss and can accurately distinguish the target and the background.