Compressed video bitstreams require protection from channel errors in a wireless channel. The three-dimensional (3-D) SPIHT coder has proved its efficiency and its real-time capability in compression of video. A forwa...
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ISBN:
(纸本)0819441880
Compressed video bitstreams require protection from channel errors in a wireless channel. The three-dimensional (3-D) SPIHT coder has proved its efficiency and its real-time capability in compression of video. A forward-error-correcting (FEC) channel (RCPC) code combined with a single ARQ (automatic-repeat-request) proved to be an effective means for protecting the bitstream. In this paper, the need for ARQ is eliminated by making the 3-D SPIHT bitstream more robust and resistant to channel errors. Packetization of the bitstream and the reorganization of these packets to achieve scalability in bit rate and/or resolution in addition to robustness is demonstrated and combined with channel coding to not only protect the integrity of the packets, but also allow detection of packet decoding failures, so that only the cleanly recovered packets are reconstructed. In extensive comparative tests, the reconstructed video is shown to be superior to that of MPEG-2, with the margin of superiority growing substantially as the channel becomes noisier.
Modulation filtering is a technique for filtering slowly-varying envelopes of frequency subbands of a non-stationary signal, ideally without affecting the signal's phase and fine-structure. Coherent modulation fil...
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ISBN:
(纸本)9780819472946
Modulation filtering is a technique for filtering slowly-varying envelopes of frequency subbands of a non-stationary signal, ideally without affecting the signal's phase and fine-structure. Coherent modulation filtering is a potentially more effective subtype of such techniques where subband envelopes are determined through demodulation of the subband signal with a coherently detected subband carrier. In this paper we propose a coherent modulation filtering technique based on detecting the instantaneous frequency of a subband from its time-frequency representation. We show that coherent modulation filtering imposes a new bandlimiting constraint on the modulation product plus the ability to recover arbitrarily chosen envelopes and carriers from their modulation product. We show that a carrier estimate based on the time-varying spectral center-of-gravity satisfies the bandlimiting condition as well as Loughlin's previously derived bandlimiting constraint on the instantaneous frequency of carrier. These bandwidth constraints lead to effective and distortion-free modulation filters, offering new approaches for potential signal modification. The spectral center-of-gravity does not satisfy the condition on arbitrary recovery, however, which somewhat limits the flexibility of coherent modulation filtering. Demonstrations are provided with speech signals.
An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is presented. These criteria aim only to produce kernels (and thus, TFRs) which will enable mo...
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ISBN:
(纸本)0819425842
An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is presented. These criteria aim only to produce kernels (and thus, TFRs) which will enable more accurate classification. We refer to these kernels, which are optimized to discriminate among several classes of signals, as signal class dependent kernels, or simply class dependent kernels. The genesis of the class dependent kernel is to be found in the area of operator theory, which we use to establish a direct link between a discrete-time, discrete-frequency TFR and its corresponding discrete signal. We see that many similarities, but also some important differences, exist between the results of the continuous-time operator approach and our discrete one. The differences between the continuous representations and discrete ones may not be the simple sampling relationship which has often been assumed. From this work, we obtain a very concise, matrix-based expression for a discrete-time/discrete-frequency TFR which is simply the product of the kernel with another matrix. This simple expression opens up the possibility to optimize the kernel in a number of ways. We focus, of course, on optimizations most suitable for classification, and ultimately wind up with the class dependent kernel. When applied to simulated sonar transient signals, we find that our approach does a good job of discriminating within very similar classes of transients and is especially sensitive to differences in time variation across classes.
Spin-image surface matching is a technique for locating objects in a scene by processing three-dimensional surface information from sources such as light detection and ranging (LIDAR), structured light photography, an...
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ISBN:
(纸本)9780819472946
Spin-image surface matching is a technique for locating objects in a scene by processing three-dimensional surface information from sources such as light detection and ranging (LIDAR), structured light photography, and tomography. It is attractive for parallel processing on graphics processing units (GPUs) because the two main computational steps matching pairs of spin-images by correlation, and matching pairs of points between model and scene - are explicitly parallel. By implementing these parallel computations on the GPU, as well as recasting serial portions of the algorithm into a parallel form and structuring the algorithm to limit data exchanges between host and GPU, this project achieved an overall speedup of 20 times or more compared to conventional serial processing. A demonstration application has been developed that allows users to select among a set of models and scenes and then applies the spin-image surface matching algorithm to match the selected models to the scene. It also has several user interface controls for changing parameters. One new parameter is a geometric consistency ratio (GCR) that quantifies the matching performance and provides a measure for discarding low-quality matches. By toggling between GPU- and host-based processing, the application demonstrates the speedup achieved with parallelization on the GPU.
An innovative approach is being used to implement and simulate the infrared (IR) and laser radar signalprocessingalgorithms for the advanced Sensor Technology Program (ASTP) and the Discrimination Interceptor Techno...
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ISBN:
(纸本)0819428221
An innovative approach is being used to implement and simulate the infrared (IR) and laser radar signalprocessingalgorithms for the advanced Sensor Technology Program (ASTP) and the Discrimination Interceptor Technology Program (DITP). Although the algorithms will run on four different computer architectures, they will use the same source code for all implementations. The initial development and testing will occur in Mathcad on a Windows 95/NT personal computer, then move to simulation on a Silicon Graphics (SGI) workstation, then to scaled real-time simulation on a parallel high performance computer (HPC), and finally to the actual flight processor, the miniaturized parallel Wafer Scale signal Processor (WSSP) with a MIMD (multiple-instruction and multiple data) architecture. This flexibility is accomplished with code wrappers that implement interchangeable interface layers for the code modules, one wrapper for Mathcad matrices, one for C++ objects on the workstation, one for message passing with static routing on the HPC, and one for dynamically routed message passing on the WSSP. With this approach, developers can move modules back and forth from the workstation simulation environment to the implementation hardware. This will eliminate the need to maintain different versions of the same algorithm. The signalprocessingalgorithms will be modified to work in a massively parallel architecture, with a message passing interface, which is simulated on the Silicon Graphics workstation, emulated on the HPC, and implemented on the WSSP. This approach will allow for pipeline processing as well as multiple, concurrently running instances of modules. In addition, innovative algorithms will fuse active laser radar detections and passive multicolor IR sensor measurements to improve target state estimation.
The next generation radar systems have high performance demands on the signalprocessing chain. Examples include the advanced image creating sensor systems in which complex calculations are to be performed on huge set...
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ISBN:
(纸本)9780769551173
The next generation radar systems have high performance demands on the signalprocessing chain. Examples include the advanced image creating sensor systems in which complex calculations are to be performed on huge sets of data in real time. Manycore architectures are gaining attention as a means to overcome the computational requirements of the complex radar signalprocessing by exploiting massive parallelism inherent in the algorithms in an energy efficient manner. In this paper, we evaluate a manycore architecture, namely a 16-core Epiphany processor, by implementing two significantly large case studies, viz. an autofocus criterion calculation and the fast factorized back-projection algorithm, both key components in modern synthetic aperture radar systems. The implementation results from the two case studies are compared on the basis of achieved performance and programmability. One of the Epiphany implementations demonstrates the usefulness of the architecture for the streaming based algorithm (the autofocus criterion calculation) by achieving a speedup of 8.9x over a sequential implementation on a state-of-the-art general-purpose processor of a later silicon technology generation and operating at a 2.7x higher clock speed. On the other case study, a highly memory-intensive algorithm (fast factorized backprojection), the Epiphany architecture shows a speedup of 4.25x. For embedded signalprocessing, low power dissipation is equally important as computational performance. In our case studies, the Epiphany implementations of the two algorithms are, respectively, 78x and 38x more energy efficient.
This Volume 2 of 2 of the conference proceedings contains 160 papers. Topics discussed include wireless communication and signalprocessing, algorithms for MIMO links, modulation and detection techniques, signal detec...
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This Volume 2 of 2 of the conference proceedings contains 160 papers. Topics discussed include wireless communication and signalprocessing, algorithms for MIMO links, modulation and detection techniques, signal detection and classification, adaptive communications and arrays, image segmentation and frequency domain processing, multiple user/multiple access techniques, digital signalprocessingarchitectures, hyperspectral processing and multisignals or data fusion, computer arithmetic implementations and FPGA designs, radar and sonar processing, equalization and synchronization techniques, higher order statistical signalprocessing for communications, adaptive signalprocessing in communication, speech coding and processing, wireless systems, special arithmetic techniques, biomedical imaging and advanced modulation and channel estimation.
A streak camera is a recording instrument in which spatial image is swept in time. creating a spatial-temporal image on a charge-coupled device (CCD). Traditional analysis for captured image data has been using unifor...
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ISBN:
(纸本)0819454974
A streak camera is a recording instrument in which spatial image is swept in time. creating a spatial-temporal image on a charge-coupled device (CCD). Traditional analysis for captured image data has been using uniform and as sampling points, in which a block of CCD pixel readouts are summed to give one reading. Equivalently simple area moving averages are applied concurrently while sampling, and high frequency content is reduced. To solve this problem. we use peak-value sampling procedure, based on the view from photoelectron statistics. After background correction. maximum values in spatial dimensions are selected to obtain time series data. A DSP filter is then applied and optimized for this time series. A Welch algorithm fast Fourier transform is applied to obtain power spectra. Segmented cumulative spectra is then calculated for global statistics and related to time domain fluctuations. Self similarity at different sweeping time-scales is used to recognize CCD pattern noise. Sinusoidal pattern noise is automatically corrected by peak-value sampling. Computational results show that time-frequency analysis using peak-value sampling algorithm and similar variants is far more effective in discovering high frequency oscillatory noise than traditional uniform binned sampling. We have applied this algorithm to analyze data produced by a 4096x4096 CCD streak camera illuminated with a macro pulse laser. High frequency oscillations in 6similar to10 GHz region were found in laser spectra. Spatial-temporal oscillations of this range are difficult to diagnose with conventional optoelectronic detectors on a per-shot basis. This work has led to improvement of laser design.
Multi-modeling is a recent tool proposed for modeling complex nonlinear systems by the use of a combination of relatively simple set of local models. Due to their simplicity, linear local models are mainly used in suc...
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ISBN:
(纸本)9789728865849
Multi-modeling is a recent tool proposed for modeling complex nonlinear systems by the use of a combination of relatively simple set of local models. Due to their simplicity, linear local models are mainly used in such structures. In this work, multi-models having polynomial local models are described and applied in system identification. Estimation of model's parameters is carried out using least squares algorithms which reduce considerably computation time as compared to iterative algorithms. The proposed methodology is applied to recurrent models implementation. NARMAX and NOE multi-models are implemented and compared to their corresponding neural network implementations. Obtained results show that the proposed recurrent multi-model architectures have many advantages over neural network models.
We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LN...
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We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LNS is the requirement to use very large ROM arrays in implementing the additions and subtraction and it limits its use to low-precision applications. MDLNS allows exponential reduction of the size of the ROMs used without affecting the speed of the computational process: moreover, the calculations over different bases and digits are completely independent, which makes this particular representation perfectly suitable for massively parallel DSP architectures. The use of more than one base has at least two extra advantages. Firstly, the proposed architecture allows us to obtain the final result straightforwardly in binary form, thus, there is no need of the exponential amplifier, used in the known LNS architectures. Secondly, the second base can be optimized in accordance to the specific digital filter characteristics. This leads to dramatic reduction of the exponents used and, consequently, to large area savings. We offer many examples showing the computational advantages of the proposed approach.
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