The article presents the concept of a universal DSP core, enabling the creation of systems compliant with various processing architectures, such as Single Instruction, Multiple Data - SIMD, Multiple Instruction, Multi...
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The article presents the concept of a universal DSP core, enabling the creation of systems compliant with various processing architectures, such as Single Instruction, Multiple Data - SIMD, Multiple Instruction, Multiple Data - MIMD. The aim was to facilitate a simpler and faster configuration and programming process for complex and more efficient signal processing systems, while minimizing the need for hardware description languages. The architecture and instruction set for the DSP core are described, allowing for simultaneous addressing of multiple operands in a single instruction. Unidirectional signal flows between cores are proposed, resulting in a reduction of connections and increased performance. The testing process and comparison of results with computations performed in Matlab are described. The paper points out future research directions, such as hardware optimization, increasing the number of cores, developing floating-point computations, and modular system construction. The proposed solutions can significantly impact the efficiency and flexibility of future signal processing systems.
A two-parameter autonomous jerk oscillator with a cosine hyperbolic nonlinearity is proposed in this paper. Firstly, the stability of equilibrium points of proposed autonomous jerk oscillator is investigated by analyz...
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A two-parameter autonomous jerk oscillator with a cosine hyperbolic nonlinearity is proposed in this paper. Firstly, the stability of equilibrium points of proposed autonomous jerk oscillator is investigated by analyzing the characteristic equation and the existence of Hopf bifurcation is verified using one of the two parameters as a bifurcation parameter. By tuning its two parameters, various dynamical behaviors are found in the proposed autonomous jerk oscillator including periodic attractor, one-scroll chaotic attractor, and coexistence between chaotic and periodic attractors. The proposed autonomous jerk oscillator has period-doubling route to chaos with the variation of one of its parameters and reverse period-doubling route to chaos with the variation of its other parameter. The proposed autonomous jerk oscillator is modelled on fieldprogrammablegatearray (FPGA) and the FPGA chip statistics and phase portraits are derived. The chaotic and coexistence of attractors generated in the proposed autonomous jerk oscillator are confirmed by FPGA implementation of the proposed autonomous jerk oscillator. A good qualitative agreement is illustrated between the numerical and FPGA results. Finally synchronization of unidirectional coupled identical proposed autonomous jerk oscillators is achieved using adaptive sliding mode control method.
With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data bring challenges for high-speed transmission and real-time processing. The general platform w...
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With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data bring challenges for high-speed transmission and real-time processing. The general platform with GPU, CPU or digital signal processor (DSP) cannot meet the requirement for short delay and low power. Therefore, a field-programmable gate array-digital signal processor (FPGA-DSP) SAR imaging accelerate platform has become a solution for processing performance with a lower latency and power. In this study, an effective mapping strategy is adopted to the FPGA-DSP hybrid heterogeneous architecture to accelerate the processing performance according to the analysis of Chirp Scaling SAR imaging algorithms. As a proof of concept, a FPGA-DSP hybrid heterogeneous accelerating platform is designed and realised. The platform requires 12 s to focus a stripmap SAR raw data with a granularity of 16,384 x 16,384.
Object location is a crucial computer vision method often used as a previous stage to object classification. Object-location algorithms require high computational and memory resources, which poses a difficult challeng...
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Object location is a crucial computer vision method often used as a previous stage to object classification. Object-location algorithms require high computational and memory resources, which poses a difficult challenge for portable and low-power devices, even when the algorithm is implemented using dedicated digital hardware. Moving part of the computation to the imager may reduce the memory requirements of the digital post-processor and exploit the parallelism available in the algorithm. This paper presents the architecture of a Smart Imaging Sensor (SIS) that performs object location using pixel-level parallelism. The SIS is based on a custom smart pixel, capable of computing frame differences in the analog domain, and a digital coprocessor that performs morphological operations and connected components to determine the bounding boxes of the detected objects. The smart-pixel array implements on-pixel temporal difference computation using analog memories to detect motion between consecutive frames. Our SIS can operate in two modes: (1) as a conventional image sensor and (2) as a smart sensor which delivers a binary image that highlights the pixels in which movement is detected between consecutive frames and the object bounding boxes. In this paper, we present the design of the smart pixel and evaluate its performance using post-parasitic extraction on a 0.35 mu m mixed-signal CMOS process. With a pixel-pitch of 32 mu m x 32 mu mu m, we achieved a fill factor of 28%. To evaluate the scalability of the design, we ported the layout to a 0.18 mu m process, achieving a fill factor of 74%. On an array of 320 x 240 smart pixels, the circuit operates at a maximum frame rate of 3846 frames per second. The digital coprocessor was implemented and validated on a Xilinx Artix-7 XC7A35T field-programmable gate array that runs at 125 MHz, locates objects in a video frame in 0.614 mu s, and has a power consumption of 58 mW.
The application of advanced technologies for engine efficiency improvement and emissions reduction also increase the occurrence possibility of abnormal combustions such as incomplete combustion, misfire, knock or pre-...
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The application of advanced technologies for engine efficiency improvement and emissions reduction also increase the occurrence possibility of abnormal combustions such as incomplete combustion, misfire, knock or pre-ignition. Novel promising combustion modes, which are basically dominated by chemical reaction kinetics show a major difficulty in combustion control. The challenge in precise combustion control is hard to overcome by the traditional engine map-based control method because it cannot monitor the combustion state of each cycle, hence, real-time cycle-resolved in-cylinder combustion diagnosis and control are required. In the past, cylinder pressure and ion current sensors, as the two most commonly used sensors for in-cylinder combustion diagnosis and control, have enjoyed a seemingly competitive relationship, so all related researches only use one of the sensors. However, these two sensors have their own unique features. In this study, the idea is to combine the information obtained from both sensors. At first, two kinds of ion current detection system are comprehensively introduced and compared at the hardware level and signal level. The most promising variant (the DC-Power ion current detection system) is selected for the subsequent experiments. Then, the concept of ion current/cylinder pressure cooperative combustion diagnosis and control system is illustrated and implemented on the engine prototyping control unit. One application case of employing this system for homogenous charge compression ignition abnormal combustion control and its stability improvement is introduced. The results show that a combination of ion current and cylinder pressure signals can provide richer and also necessary information for combustion control. Finally, ion current and cylinder pressure signals are employed as inputs of artificial neural network (ANN) models for combustion prediction. The results show that the combustion prediction performance is better when the inputs ar
作者:
Viola, FabioUniv Palermo
DEIM Dipartimento Energia Ingn Informaz & Modelli Mate I-90133 Palermo Italy
Over the last decades, plants devoted to the generation of green energy significantly increased their number, together with the demand of same electrical energy, also stored in battery systems. This fact produced the ...
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Over the last decades, plants devoted to the generation of green energy significantly increased their number, together with the demand of same electrical energy, also stored in battery systems. This fact produced the growth of energy conversion systems with advanced performances with respect to the traditional ones. In this circumstance, multilevel converters play a significant role for their great advantages in performances, flexibility, fault-tolerability, employment of renewable energy sources and storage systems and finally yet importantly reduced filter requirements. In this context, this paper faces the performance of a cascaded H-bridge 5 level inverter in terms of harmonic distortion generated and injected into the grid. Through an accurate analysis that takes into account the pulse width modulation (PWM) multicarrier modulation techniques (phase disposition PD, phase opposition disposition POD, alternative phase opposition disposition APOD, phase shifted PS) and related reference signals (sinusoidal reference;third harmonic injection THI reference, switching frequency optimal SFO reference), a framework of distorting harmonics is presented by comparing twelve cases. The results obtained from the simulations are reproduced and validated in a prototype system of five level cascaded H-bridge multilevel inverter. A deep discussion of control and filtering system is provided to justify the choice of the best modulation technique to adopt.
A nonvolatile lookup table (NV-LUT) circuit, which is a key component of a field-programmable gate array, is proposed for an energy-efficient yet high-performance binarized convolutional neural network (BCNN) accelera...
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A nonvolatile lookup table (NV-LUT) circuit, which is a key component of a field-programmable gate array, is proposed for an energy-efficient yet high-performance binarized convolutional neural network (BCNN) accelerator. Since the active load is distributed to each configuration memory cell, the effect of the parasitic components is greatly reduced. Moreover, the use of a wired-OR logic-circuit style makes it possible to perform a high-speed logic operation. The proposed 6-input NV-LUT circuit using an active-load-localized single-ended circuit style is designed using a 45 nm CMOS technology and the delay is reduced by 30% with only 13% of hardware overhead compared to those of a conventional NV-LUT circuit. It is also demonstrated that the proposed NV-LUT circuit exhibits variation resilience against three process corners. The use of the proposed NV-LUT circuit also makes it possible to reduce 47% of the energy consumption of a BCNN accelerator for digit recognition compared to that of a conventional SRAM-LUT-based implementation.
We report the results of the analysis of experiments on dynamic phase correction of laser radiation distorted by a turbulent airflow in an adaptive optical system (AOS) with a Shack - Hartmann wavefront sensor (WFS). ...
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We report the results of the analysis of experiments on dynamic phase correction of laser radiation distorted by a turbulent airflow in an adaptive optical system (AOS) with a Shack - Hartmann wavefront sensor (WFS). A field-programmable gate array is used as the main AOS control element, which provides a closed loop AOS bandwidth of up to 2000 Hz. The WFS is used to estimate the characteristic bandwidth of the generated turbulence nu(turb). Changes in the spatial and temporal spectra of the laser radiation phase, as well as the quality of the beam during its dynamic phase correction at various AOS frequencies, are analysed. It is shown experimentally and by calculation that to ensure a high efficiency of the wavefront correction, the AOS frequency should be at least 20 times higher than nu(turb).
Energy is the main engine and the active element for all growth and development. It is the basic element for all sectors of the economy and a companion to human life. It is also not forgotten that most of the energy u...
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Energy is the main engine and the active element for all growth and development. It is the basic element for all sectors of the economy and a companion to human life. It is also not forgotten that most of the energy used in the whole world is traditional and unsustainable energy, as well as polluting the environment and causing harmful emissions. Sustainable is based primarily on environmental protection. Massive population growth is accompanied by a significant increase in energy consumption. Currently, most countries are turning to rely mainly on renewable energy sources. To achieve the maximum benefit from the energy, the tendency is to manage energy within the home to avoid the occurrence of energy losses. In this paper, an efficient home energy management system (HEMS) is proposed. This system is based on the use of a field-programmable gate array (FPGA) for home energy management. The proposed HEMS takes into account both generation and consumption as FPGA manages the feeding process through the sources. The prototype is implemented using Altera Cyclone IV EP4CE6 FPGA board using QUARTUS II software. The home is fed through PV, wind and fuel cells (FC) sources. If there is a shortage in energy production and the three sources are unable to cover the loads, the batteries enter into service to cover this shortage. If the sources and batteries are unable to cover the required loads, the EV contributes to covering the load, but with specific constraints set by the owner. The proposed HEMS works to control the feeding of the loads, as it schedules the feeding of the loads according to priority in the event of severe energy shortages and the inability of the sources, batteries and the EV to cover the loads. The experimental and simulation results proved the ability of the proposed system to respond to the demand by managing high energy consuming household appliances according to the pre-set priority.
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