44 research outputs found

    A Programmable look-up table-based interpolator with nonuniform sampling scheme

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    Interpolation is a useful technique for storage of complex functions on limited memory space: some few sampling values are stored on a memory bank, and the function values in between are calculated by interpolation. This paper presents a programmable Look-Up Table-based interpolator, which uses a reconfigurable nonuniform sampling scheme: the sampled points are not uniformly spaced. Their distribution can also be reconfigured to minimize the approximation error on specific portions of the interpolated function's domain. Switching from one set of configuration parameters to another set, selected on the fly from a variety of precomputed parameters, and using different sampling schemes allow for the interpolation of a plethora of functions, achieving memory saving and minimum approximation error. As a study case, the proposed interpolator was used as the core of a programmable noise generatoroutput signals drawn from different Probability Density Functions were produced for testing FPGA implementations of chaotic encryption algorithms. As a result of the proposed method, the interpolation of a specific transformation function on a Gaussian noise generator reduced the memory usage to 2.71% when compared to the traditional uniform sampling scheme method, while keeping the approximation error below a threshold equal to 0.000030518

    Multirate digital filters, filter banks, polyphase networks, and applications: a tutorial

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    Multirate digital filters and filter banks find application in communications, speech processing, image compression, antenna systems, analog voice privacy systems, and in the digital audio industry. During the last several years there has been substantial progress in multirate system research. This includes design of decimation and interpolation filters, analysis/synthesis filter banks (also called quadrature mirror filters, or QMFJ, and the development of new sampling theorems. First, the basic concepts and building blocks in multirate digital signal processing (DSPJ, including the digital polyphase representation, are reviewed. Next, recent progress as reported by several authors in this area is discussed. Several applications are described, including the following: subband coding of waveforms, voice privacy systems, integral and fractional sampling rate conversion (such as in digital audio), digital crossover networks, and multirate coding of narrow-band filter coefficients. The M-band QMF bank is discussed in considerable detail, including an analysis of various errors and imperfections. Recent techniques for perfect signal reconstruction in such systems are reviewed. The connection between QMF banks and other related topics, such as block digital filtering and periodically time-varying systems, based on a pseudo-circulant matrix framework, is covered. Unconventional applications of the polyphase concept are discussed

    High Performance Non-uniform FFT on Modern x86-based Multi-core Systems

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    Abstract-The Non-Uniform Fast Fourier Transform (NUFFT) is a generalization of FFT to non-equidistant samples. It has many applications which vary from medical imaging to radio astronomy to the numerical solution of partial differential equations. Despite recent advances in speeding up NUFFT on various platforms, its practical applications are still limited, due to its high computational cost, which is significantly dominated by the convolution of a signal between a nonuniform and uniform grids. The computational cost of the NUFFT is particularly detrimental in cases which require fast reconstruction times, such as iterative 3D non-Cartesian MRI reconstruction. We propose novel and highly scalable parallel algorithm for performing NUFFT on x86-based multi-core CPUs. The high performance of our algorithm relies on good SIMD utilization and high parallel efficiency. On convolution, we demonstrate on average 90% SIMD efficiency using SSE, as well up to linear scalability using a quad-socket 40-core Intel R Xeon R E7-4870 Processors based system. As a result, on dual socket Intel R Xeon R X5670 based server, our NUFFT implementation is more than 4x faster compared to the best available NUFFT3D implementation, when run on the same hardware. On Intel R Xeon R E5-2670 processor based server, our NUFFT implementation is 1.5X faster than any published NUFFT implementation today. Such speed improvement opens new usages for NUFFT. For example, iterative multichannel reconstruction of a 240x240x240 image could execute in just over 3 minutes, which is on the same order as contemporary non-iterative (and thus less-accurate) 3D NUFFT-based MRI reconstructions

    Digital signal processing in radio receivers and transmitters

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    The interface between analog and digital signal processing paths in radio receivers and transmitters is steadily migrating toward the antenna as engineers learn to combine the unique attributes and capabilities of DSP with those of traditional communication system designs to achieve system s with superior and broadened capabilities while reducing system cost. Digital signal processing (DSP) techniques are rapidly being applied to many signal conditioning and signal processing tasks traditionally performed by analog components and subsystems in RF communication receivers and transmitters [1±4]. The incentive to replace analog implementations of signal processing functions with DSP-based processing includes reduced cost, enhanced performance, improved reliability, ease of manufacturing and maintenance, and operating ¯exibility and con® gurabilit

    Electronics for Sensors

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    The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

    Filter Bank Multicarrier Modulation for Spectrally Agile Waveform Design

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    In recent years the demand for spectrum has been steadily growing. With the limited amount of spectrum available, Spectrum Pooling has gained immense popularity. As a result of various studies, it has been established that most of the licensed spectrum remains underutilized. Spectrum Pooling or spectrum sharing concentrates on making the most of these whitespaces in the licensed spectrum. These unused parts of the spectrum are usually available in chunks. A secondary user looking to utilize these chunks needs a device capable of transmitting over distributed frequencies, while not interfering with the primary user. Such a process is known as Dynamic Spectrum Access (DSA) and a device capable of it is known as Cognitive Radio. In such a scenario, multicarrier communication that transmits data across the channel in several frequency subcarriers at a lower data rate has gained prominence. Its appeal lies in the fact that it combats frequency selective fading. Two methods for implementing multicarrier modulation are non-contiguous orthogonal frequency division multiplexing (NCOFDM)and filter bank multicarrier modulation (FBMC). This thesis aims to implement a novel FBMC transmitter using software defined radio (SDR) with modulated filters based on a lowpass prototype. FBMCs employ two sets of bandpass filters called analysis and synthesis filters, one at the transmitter and the other at the receiver, in order to filter the collection of subcarriers being transmitted simultaneously in parallel frequencies. The novel aspect of this research is that a wireless transmitter based on non-contiguous FBMC is being used to design spectrally agile waveforms for dynamic spectrum access as opposed to the more popular NC-OFDM. Better spectral containment and bandwidth efficiency, combined with lack of cyclic prefix processing, makes it a viable alternative for NC-OFDM. The main aim of this thesis is to prove that FBMC can be practically implemented for wireless communications. The practicality of the method is tested by transmitting the FBMC signals real time by using the Simulink environment and USRP2 hardware modules

    Optimized techniques for real-time microwave and millimeter wave SAR imaging

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    Microwave and millimeter wave synthetic aperture radar (SAR)-based imaging techniques, used for nondestructive evaluation (NDE), have shown tremendous usefulness for the inspection of a wide variety of complex composite materials and structures. Studies were performed for the optimization of uniform and nonuniform sampling (i.e., measurement positions) since existing formulations of SAR resolution and sampling criteria do not account for all of the physical characteristics of a measurement (e.g., 2D limited-size aperture, electric field decreasing with distance from the measuring antenna, etc.) and nonuniform sampling criteria supports sampling below the Nyquist rate. The results of these studies demonstrate optimum sampling given design requirements that fully explain resolution dependence on sampling criteria. This work was then extended to manually-selected and nonuniformly distributed samples such that the intelligence of the user may be utilized by observing SAR images being updated in real-time. Furthermore, a novel reconstruction method was devised that uses components of the SAR algorithm to advantageously exploit the inherent spatial information contained in the data, resulting in a superior final SAR image. Furthermore, better SAR images can be obtained if multiple frequencies are utilized as compared to single frequency. To this end, the design of an existing microwave imaging array was modified to support multiple frequency measurement. Lastly, the data of interest in such an array may be corrupted by coupling among elements since they are closely spaced, resulting in images with an increased level of artifacts. A method for correcting or pre-processing the data by using an adaptation of correlation canceling technique is presented as well --Abstract, page iii

    The BrightEyes-TTM: an open-source time-tagging module for fluorescence lifetime imaging microscopy applications

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    The aim of this Ph.D. work is to reason and show how an open-source multi-channel and standalone time-tagging device was developed, validated and used in combination with a new generation of single-photon array detectors to pursue super-resolved time-resolved fluorescence lifetime imaging measurements. Within the compound of time-resolved fluorescence laser scanning microscopy (LSM) techniques, fluorescence lifetime imaging microscopy (FLIM) plays a relevant role in the life-sciences field, thanks to its ability of detecting functional changes within the cellular micro-environment. The recent advancements in photon detection technologies, such as the introduction of asynchronous read-out single-photon avalanche diode (SPAD) array detectors, allow to image a fluorescent sample with spatial resolution below the diffraction limit, at the same time, yield the possibility of accessing the single-photon information content allowing for time-resolved FLIM measurements. Thus, super-resolved FLIM experiments can be accomplished using SPAD array detectors in combination with pulsed laser sources and special data acquisition systems (DAQs), capable of handling a multiplicity of inputs and dealing with the single-photons readouts generated by SPAD array detectors. Nowadays, the commercial market lacks a true standalone, multi-channel, single-board, time-tagging and affordable DAQ device specifically designed for super-resolved FLIM experiments. Moreover, in the scientific community, no-efforts have been placed yet in building a device that can compensate such absence. That is why, within this Ph.D. project, an open-source and low-cost device, the so-called BrightEyes-TTM (time tagging module), was developed and validated both for fluorescence lifetime and time-resolved measurements in general. The BrightEyes-TTM belongs to a niche of DAQ devices called time-to-digital converters (TDCs). The field-gate programmable array (FPGA) technology was chosen for implementing the BrightEyes-TTM thanks to its reprogrammability and low cost features. The literature reports several different FPGA-based TDC architectures. Particularly, the differential delay-line TDC architecture turned out to be the most suitable for this Ph.D. project as it offers an optimal trade-off between temporal precision, temporal range, temporal resolution, dead-time, linearity, and FPGA resources, which are all crucial characteristics for a TDC device. The goal of the project of pursuing a cost-effective and further-upgradable open-source time-tagging device was achieved as the BrigthEyes-TTM was developed and assembled using low-cost commercially available electronic development kits, thus allowing for the architecture to be easily reproduced. BrightEyes-TTM was deployed on a FPGA development board which was equipped with a USB 3.0 chip for communicating with a host-processing unit and a multi-input/output custom-built interface card for interconnecting the TTM with the outside world. Licence-free softwares were used for acquiring, reconstructing and analyzing the BrightEyes-TTM time-resolved data. In order to characterize the BrightEyes-TTM performances and, at the same time, validate the developed multi-channel TDC architecture, the TTM was firstly tested on a bench and then integrated into a fluorescent LSM system. Yielding a 30 ps single-shot precision and linearity performances that allows to be employed for actual FLIM measurements, the BrightEyes-TTM, which also proved to acquire data from many channels in parallel, was ultimately used with a SPAD array detector to perform fluorescence imaging and spectroscopy on biological systems. As output of the Ph.D. work, the BrightEyes-TTM was released on GitHub as a fully open-source project with two aims. The principal aim is to give to any microscopy and life science laboratory the possibility to implement and further develop single-photon-based time-resolved microscopy techniques. The second aim is to trigger the interest of the microscopy community, and establish the BrigthEyes-TTM as a new standard for single-photon FLSM and FLIM experiments

    Earth Observatory Satellite system definition study. Report no. 3: Design/cost tradeoff studies. Appendix D: EOS configuration design data. Part 2: Data management system configuration

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    The Earth Observatory Satellite (EOS) data management system (DMS) is discussed. The DMS is composed of several subsystems or system elements which have basic purposes and are connected together so that the DMS can support the EOS program by providing the following: (1) payload data acquisition and recording, (2) data processing and product generation, (3) spacecraft and processing management and control, and (4) data user services. The configuration and purposes of the primary or high-data rate system and the secondary or local user system are explained. Diagrams of the systems are provided to support the systems analysis

    Streaming Architectures for Medical Image Reconstruction

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    Non-invasive imaging modalities have recently seen increased use in clinical diagnostic procedures. Unfortunately, emerging computational imaging techniques, such as those found in 3D ultrasound and iterative magnetic resonance imaging (MRI), are severely limited by the high computational requirements and poor algorithmic efficiency in current arallel hardware---often leading to significant delays before a doctor or technician can review the image, which can negatively impact patients in need of fast, highly accurate diagnosis. To make matters worse, the high raw data bandwidth found in 3D ultrasound requires on-chip volume reconstruction with a tight power dissipation budget---dissipation of more than 5~W may burn the skin of the patient. The tight power constraints and high volume rates required by emerging applications require orders of magnitude improvement over state-of-the-art systems in terms of both reconstruction time and energy efficiency. The goal of the research outlined in this dissertation is to reduce the time and energy required to perform medical image reconstruction through software/hardware co-design. By analyzing algorithms with a hardware-centric focus, we develop novel algorithmic improvements which simultaneously reduce computational requirements and map more efficiently to traditional hardware architectures. We then design and implement hardware accelerators which push the new algorithms to their full potential. In the first part of this dissertation, we characterize the performance bottlenecks of high-volume-rate 3D ultrasound imaging. By analyzing the 3D plane-wave ultrasound algorithm, we reduce computational and storage requirements in Delay Compression. Delay Compression recognizes additional symmetry in the planar transmission scheme found in 2D, 3D, and 3D-Separable plane-wave ultrasound implementations, enabling on-chip storage of the reconstruction constants for the first time and eliminating the ost power-intensive component of the reconstruction process. We then design and implement Tetris, a streaming hardware accelerator for 3D-Separable plane-wave ultrasound. Tetris is enabled by the Tetris Reserveration Station, a novel 2D register file that buffers incomplete voxels and eliminates the need for a traditional load-and-store memory interface. Utilizing a fully pipelined architecture, Tetris reconstructs volumes at physics-limited rates (i.e., limited by the physical propagation speed of sound through tissue). Next, we review a core component of several computational imaging modalities, the Non-uniform Fast Fourier Transform (NuFFT), focusing on its use in MRI reconstruction. We find that the non-uniform interpolation step therein requires over 99% of the reconstruction time due to poor spatial and temporal memory locality. While prior work has made great strides in improving the performance of the NuFFT, the most common algorithmic optimization severely limits the available parallelism, causing it to map poorly to the massively parallel processing available in modern GPUs and FPGAs. To this end, we create Slice-and-Dice, a processing model which enables efficient mapping of the NuFFT's most computationally-intensive component onto traditional parallel architectures. We then demonstrate the full acceleration potential of Slice-and-Dice with Jigsaw, a custom hardware accelerator which performs the non-uniform interpolations found in the NuFFT in time approximately linear in the number of non-uniform samples, rrespective of sampling pattern, uniform grid size, or interpolation kernel width. The algorithms and architectures herein enable faster, more efficient medical image reconstruction, without sacrificing image quality. By decreasing the time and energy required for image reconstruction, our work opens the door for future exploration into higher-resolution imaging and emerging, computationally complex reconstruction algorithms which improve the speed and quality of patient diagnosis.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/167986/1/westbl_1.pd
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