NASA Technical Reports Server (Ntrs) 20040171233: a Discussion of Using a Reconfigurable Processor to Implement the Discrete Fourier Transform by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20040171233: a Discussion of Using a Reconfigurable Processor to Implement the Discrete Fourier Transform by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20060017831: a Plug and Play Gnc Architecture Using Fpga Components by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20060017831: a Plug and Play Gnc Architecture Using Fpga Components by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20050237977: Design of the Protocol Processor for the Robus-2 Communication System by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20050237977: Design of the Protocol Processor for the Robus-2 Communication System by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20050206351: a Vhdl Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback by NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 20050206351: a Vhdl Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback by NASA Technical Reports Server (Ntrs); published by
Binary and ternary adders are frequently used to speed-up many digital signal processing (DSP) operations like multiplication, compression, filtering, convolution, etc. FPGA realization of these circuits uses a combin...
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Binary and ternary adders are frequently used to speed-up many digital signal processing (DSP) operations like multiplication, compression, filtering, convolution, etc. FPGA realization of these circuits uses a combination of look-up tables (LUTs) and carry-chains. Alternatively, inbuilt operators and parameterizable IP cores provide an efficient means of implementing these circuits. However, the realization is not optimal in the sense that the full potential of the underlying resources is not utilized. In this paper, we use technology-dependent approaches to restructure the Boolean networks corresponding to these circuits. The restructured networks are then mapped optimally onto the FPGA fabric using minimum possible resources. Our analysis shows a subsequent speed-up in the performance of these circuits when compared to different conventional and existing approaches.
This paper presents a programmable system-on-chip implementation to be used for acceleration of computations within hidden Markov models. The high level synthesis (HLS) and "divide-and-conquer" approaches ar...
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This paper presents a programmable system-on-chip implementation to be used for acceleration of computations within hidden Markov models. The high level synthesis (HLS) and "divide-and-conquer" approaches are presented for parallelization of Baum-Welch and Viterbi algorithms. To avoid arithmetic underflows, all computations are performed within the logarithmic space. Additionally, in order to carry out computations efficiently - i.e. directly in an FPGA system or a processor cache - we postulate to reduce the floating-point representations of HMMs. We state and prove a lemma about the length of numerically unsafe sequences for such reduced precision models. Finally, special attention is devoted to the design of a multiple logarithm and exponent approximation unit (MLEAU). Using associative mapping, this unit allows for simultaneous conversions of multiple values and thereby compensates for computational efforts of logarithmic-space operations. Design evaluation reveals absolute stall delay occurring by multiple hardware conversions to logarithms and to exponents, and furthermore the experiments evaluation reveals HMMs computation boundaries related to their probabilities and floating-point representation. The performance differences at each stage of computation are summarized in performance comparison between hardware acceleration using MLEAU and typical software implementation on an ARM or Intel processor.
Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often...
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Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Using a field-programmablegate array (FPGA) development board, a digital signal processor (DSP) builder, and the phase-to-amplitude conversion principle, a low-cost system for measuring the amplitude-to-amplitude (AM...
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Using a field-programmablegate array (FPGA) development board, a digital signal processor (DSP) builder, and the phase-to-amplitude conversion principle, a low-cost system for measuring the amplitude-to-amplitude (AM/AM) and amplitude-to-phase (AM/PM) distortion curves of radio frequency (RF) power amplifiers (PAs) is presented. The state of the art based on the measurements and preliminary studies of AM/AM and AM/PM distortion curves is discussed. A full digital control of the test bed simulated/emulated in Matlab/Simulink is introduced to recalculate the known AM/AM and AM/PM measurements stored as look-up table (LUT). Finally, the low-cost system comprises the memory polynomial model (MPM) that involves the nonlinearity order and memory effects of real PAs. (C) 2015 Elsevier B.V. All rights reserved.
Sound localization systems are widely studied and have several potential applications, including hearing aid devices, surveillance and robotics. However, few proposed solutions target portable systems, such as wearabl...
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Sound localization systems are widely studied and have several potential applications, including hearing aid devices, surveillance and robotics. However, few proposed solutions target portable systems, such as wearable devices, which require a small unnoticeable platform, or unmanned aerial vehicles, in which weight and low power consumption are critical aspects. The main objective of this research is to achieve real-time sound localization capability in a small, self-contained device, without having to rely on large shaped platforms or complex microphone arrays. The proposed device has two surface-mount microphones spaced only 20 mm apart. Such reduced dimensions present challenges for the implementation, as differences in level and spectra become negligible, and only time-difference of arrival (TDoA) can be used as a localization cue. Three main issues have to be addressed in order to accomplish these objectives. To achieve real-time processing, the TDoA is calculated using zero-crossing spikes applied to the hardware-friendly Jeffers model. In order to make up for the reduction in resolution due to the small dimensions, the signal is upsampled several-fold within the system. Finally, a coherence-based spectral masking is used to select only frequency components with relevant TDoA information. The proposed system was implemented on a field-programmablegate array (FPGA) based platform, due to the large amount of concurrent and independent tasks, which can be efficiently parallelized in reconfigurable hardware devices. Experimental results with white-noise and environmental sounds show high accuracies for both anechoic and reverberant conditions.
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