35,032 research outputs found
Speeding up Convolutional Neural Networks with Low Rank Expansions
The focus of this paper is speeding up the evaluation of convolutional neural
networks. While delivering impressive results across a range of computer vision
and machine learning tasks, these networks are computationally demanding,
limiting their deployability. Convolutional layers generally consume the bulk
of the processing time, and so in this work we present two simple schemes for
drastically speeding up these layers. This is achieved by exploiting
cross-channel or filter redundancy to construct a low rank basis of filters
that are rank-1 in the spatial domain. Our methods are architecture agnostic,
and can be easily applied to existing CPU and GPU convolutional frameworks for
tuneable speedup performance. We demonstrate this with a real world network
designed for scene text character recognition, showing a possible 2.5x speedup
with no loss in accuracy, and 4.5x speedup with less than 1% drop in accuracy,
still achieving state-of-the-art on standard benchmarks
Fractional biorthogonal partners in channel equalization and signal interpolation
The concept of biorthogonal partners has been introduced recently by the authors. The work presented here is an extension of some of these results to the case where the upsampling and downsampling ratios are not integers but rational numbers, hence, the name fractional biorthogonal partners. The conditions for the existence of stable and of finite impulse response (FIR) fractional biorthogonal partners are derived. It is also shown that the FIR solutions (when they exist) are not unique. This property is further explored in one of the applications of fractional biorthogonal partners, namely, the fractionally spaced equalization in digital communications. The goal is to construct zero-forcing equalizers (ZFEs) that also combat the channel noise. The performance of these equalizers is assessed through computer simulations. Another application considered is the all-FIR interpolation technique with the minimum amount of oversampling required in the input signal. We also consider the extension of the least squares approximation problem to the setting of fractional biorthogonal partners
An Improved Variable Structure Adaptive Filter Design and Analysis for Acoustic Echo Cancellation
In this research an advance variable structure adaptive Multiple Sub-Filters (MSF) based algorithm for single channel Acoustic Echo Cancellation (AEC) is proposed and analyzed. This work suggests a new and improved direction to find the optimum tap-length of adaptive filter employed for AEC. The structure adaptation, supported by a tap-length based weight update approach helps the designed echo canceller to maintain a trade-off between the Mean Square Error (MSE) and time taken to attain the steady state MSE. The work done in this paper focuses on replacing the fixed length sub-filters in existing MSF based AEC algorithms which brings refinements in terms of convergence, steady state error and tracking over the single long filter, different error and common error algorithms. A dynamic structure selective coefficient update approach to reduce the structural and computational cost of adaptive design is discussed in context with the proposed algorithm. Simulated results reveal a comparative performance analysis over proposed variable structure multiple sub-filters designs and existing fixed tap-length sub-filters based acoustic echo cancellers
Design and evaluation of a filter spectrometer concept for facsimile cameras
The facsimile camera is an optical-mechanical scanning device which was selected as the imaging system for the Viking '75 lander missions to Mars. A concept which uses an interference filter-photosensor array to integrate a spectrometric capability with the basic imagery function of this camera was proposed for possible application to future missions. This paper is concerned with the design and evaluation of critical electronic circuits and components that are required to implement this concept. The feasibility of obtaining spectroradiometric data is demonstrated, and the performance of a laboratory model is described in terms of spectral range, angular and spectral resolution, and noise-equivalent radiance
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