One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse rep...
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Abundance fully constrained least squares (FLCS) method has been widely used for spectral unmixing. A modified FCLS (MFCLS) was previously proposed for the same purpose to derive two iterative equations for solving fu...
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This paper introduces a new method to track articulator movements, specifically jaw position and angle, using 5 degree of freedom (5 DOF) orientation data. The approach uses a quaternion rotation method to accomplish ...
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This paper describes a unique cross-phoneme speaker identification experiment, using deliberately mismatched phoneme sets for training and testing. The underlying goal is to identify features that represent broad indi...
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ISBN:
(纸本)9781467301732
This paper describes a unique cross-phoneme speaker identification experiment, using deliberately mismatched phoneme sets for training and testing. The underlying goal is to identify features that represent broad individually unique characteristics rather than those that represent phonetic differences, as are more typical of modern speaker identification and verification systems. A wide range of features are proposed and evaluated within this context using a Gaussian Mixture Model framework. The results show that log-area ratio has better phonetic independence than MFCCs, that residual phase carries substantial speaker information, and identifies several other features that also have usefulness for speaker identification independent of phonetic content.
This paper investigates the problem of designing a nonlinear state feedback controller for a class of uncertain polynomial discrete-time systems using rational Lyapunov functions. The uncertainty that under considerat...
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The recent evolution of many-core architectures has resulted in chips where the number of processor elements (PEs) are in the hundreds and continue to increase every day. In addition, many-core processors are more and...
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ISBN:
(纸本)9781467309745
The recent evolution of many-core architectures has resulted in chips where the number of processor elements (PEs) are in the hundreds and continue to increase every day. In addition, many-core processors are more and more frequently characterized by the diversity of their resources and the way the sharing of those resources is arbitrated. On such machines, task scheduling is of paramount importance to orchestrate a satisfactory distribution of tasks with an efficient utilization of resources, especially when fine-grain parallelism is desired or required. In the past, the primary focus of scheduling techniques has been on achieving load balancing and reducing overhead with the aim to increase total performance. This focus has resulted in a scheduling paradigm where Static Scheduling (SS) is preferred to Dynamic Scheduling (DS) for highly regular and embarrassingly parallel applications running on homogeneous architectures. We have revisited the task scheduling problem for these types of applications under the scenario imposed by many-core architectures to investigate whether or not there exists scenarios where DS is better than SS. Our main contribution is the idea that, for highly regular and embarrassingly parallel applications, DS is preferable to SS in some situations commonly found in many-core architectures. We present experimental evidence that shows how the performance of SS is degraded by the new environment on many-core chips. We analyze three reasons that contribute to the superiority of DS over SS on many-core architectures under the situations described: 1) A uniform mapping of work to processors without considering the granularity of tasks is not necessarily scalable under limited amounts of work. 2) The presence of shared resources (i.e. the crossbar switch) produces unexpected and stochastic variations on the duration of tasks that SS is unable to manage properly. 3) Hardware features, such as in-memory atomic operations, greatly contribute to decrea
Transform coding is a widely used image compression technique, where entropy reduction can be achieved by decomposing the image over a dictionary which provides compaction. Existing algorithms, such as JPEG and JPEG20...
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Transform coding is a widely used image compression technique, where entropy reduction can be achieved by decomposing the image over a dictionary which provides compaction. Existing algorithms, such as JPEG and JPEG2000, utilize fixed dictionaries which are shared by the encoder and decoder. Recently, works utilizing content-specific dictionaries show promising results by focusing on specific classes of images and using highly specialized dictionaries. However, such approaches lose the ability to compress arbitrary images. In this paper we propose an input-adaptive compression approach, which encodes each input image over a dictionary specifically trained for it. The scheme is based on the sparse dictionary structure, whose compact representation allows relatively low-cost transmission of the dictionary along with the compressed data. In this way, the process achieves both adaptivity and generality. Our results show that although this method involves transmitting the dictionary, it remains competitive with the JPEG and JPEG2000 algorithms.
The mode decision process has a significant effect on the quality and complexity of a video encoder. The conventional method that fully codes each macro block for different modes results in the best quality performanc...
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We, for the first time, estimate total fluctuation resulting from random dopants, interface traps and work functions using experimentally calibrated 3D statistical device simulation on 16-nm-gate high-κ/metal gate pl...
We, for the first time, estimate total fluctuation resulting from random dopants, interface traps and work functions using experimentally calibrated 3D statistical device simulation on 16-nm-gate high-κ/metal gate planar and bulk FinFET devices. The total full 3D simulated threshold voltage fluctuation (σV th ), induced by the aforementioned random sources simultaneously, is different from their statistical total sum because the assumption of independently and identically distributed random variables is invalid owing to strong surface potential's interactions among them. Structural innovation using bulk FinFET implies significant fluctuation suppression, which is about 45.6% reduction on σV th . 3D vertical channel-based device provides good capability in fluctuation reduction, compared with process efforts on low interface trap density (e.g., D it is below 10 11 eV -1 cm -2 ) and small grain size (e.g., 1×1 nm 2 ) of metal gate on planar one.
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