1223138
Efficient Continuous HRTF Model Using Data Independent Basis Functions: Experimentally Guided Approach
This paper introduces a continuous functional model for head-related transfer functions (HRTFs) in the horizontal auditory scene. The approach uses a separable representation consisting of a Fourier-Bessel series expansion for the spectral components and a conventional Fourier series expansion for the spatial components. Being independent of the data, these two sets of basis functions remain unchanged for all subjects and measurement setups. Hence, the model can transform an individualized HRTF to a subject specific set of coefficients. A continuous functional model is also developed in the time domain. We show the efficient model performance in approximating experimental measurements by using the HRTF measurements from a KEMAR manikin and the synthetic data from the spherical head model. The statistical results are determined from a 50-subject HRTF data set. We also corroborate the predictive capability of the proposed model. The model has near optimal performance, which can be ascertained by comparison with the standard principle component analysis (PCA) and discrete Karhunen-Loeve expansion (KLE) methods at the measurement points and for a given number of parameters.
16445226
Modal expansion of HRTFs: Continuous representation in frequency-range-angle
This paper proposes a continuous HRTF representation in both 3D spatial and frequency domains. The method is based on the acoustic reciprocity principle and a modal expansion of the wave equation solution to represent the HRTF variations with different variables in separate basis functions. The derived spatial basis modes can achieve HRTF near-field and far-field representation in one formulation. The HRTF frequency components are expanded using Fourier Spherical Bessel series for compact representation. The proposed model can be used to reconstruct HRTFs at any arbitrary position in space and at any frequency point from a finite number of measurements. Analytical simulated and measured HRTFs from a KEMAR are used to validate the model.
12929858
UWB Spatia - Frequency Channel Characterization
This paper investigates the spatial-frequency channel characterization of ultra-wideband (UWB) wireless communication systems. First, a novel frequency dependent UWB channel model is constructed based on the theory of electromagnetic diffraction mechanism, which causes the field strength to vary with the frequency in each multipath. Then, we build a space-frequency model, which includes spatial characteristics such as angular power spectrum, and physical sampling points in space. The space-frequency model has two special cases (i) discrete multipath model, and (ii) cluster model, which can be readily used to generate channel data for any arbitrary set of sensor locations. The reconstruction results from channel measurements show the accurateness of the novel frequency dependent model, with reconstruction error decreasing by 40%, compared to the traditional Turin model
12737974
The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search
To investigate how top-down (TD) and bottom-up (BU) information is weighted in the guidance of human search behavior, we manipulated the proportions of BU and TD components in a saliency-based model. The model is biologically plausible and implements an artificial retina and a neuronal population code. The BU component is based on feature-contrast. The TD component is defined by a feature-template match to a stored target representation. We compared the model's behavior at different mixtures of TD and BU components to the eye movement behavior of human observers performing the identical search task. We found that a purely TD model provides a much closer match to human behavior than any mixture model using BU information. Only when biological constraints are removed (e.g., eliminating the retina) did a BU/TD mixture model begin to approximate human behavior.
8356979
Real-time Accurate Object Detection using Multiple Resolutions
We propose a multi-resolution framework inspired by human visual search for general object detection. Different resolutions are represented using a coarse-to-fine feature hierarchy. During detection, the lower resolution features are initially used to reject the majority of negative windows at relatively low cost, leaving a relatively small number of windows to be processed in higher resolutions. This enables the use of computationally more expensive higher resolution features to achieve high detection accuracy. We applied this framework on Histograms of Oriented Gradient (HOG) features for object detection. Our multi-resolution detector produced better performance for pedestrian detection than state-of-the-art methods (Dalal and Triggs, 2005), and was faster during both training and testing. Testing our method on motorbikes and cars from the VOC database revealed similar improvements in both speed and accuracy, suggesting that our approach is suitable for realtime general object detection applications.
11047452
Compiler-directed management of instruction accesses
We present a compiler-oriented strategy to reduce the memory system energy consumption due to instruction accesses and increase performance by exploiting scratch pad memories. Scratch pad memories (SPMs) are alternatives to conventional cache memories in embedded computing. These small on-chip memories, like caches, provide fast and low-power access to data and instructions; but, they differ from caches in that their contents are managed by software instead of hardware. Our compiler framework keeps the most frequently used instructions in SPM and dynamically changes the contents of the SPM as the (instruction) working set of the application changes.
18870044
Reducing data cache leakage energy using a compiler-based approach
Silicon technology advances have made it possible to pack millions of transistors---switching at high clock speeds---on a single chip. While these advances bring unprecedented performance to electronic products, they also pose difficult power/energy consumption problems. For example, large number of transistors in dense on-chip cache memories consume significant static (leakage) power even if the cache is not used by the current computation. While previous compiler research studied code and data restructuring for improving data cache performance, to our knowledge, there exists no compiler-based study that targets data cache leakage power consumption. In this paper, we present code restructuring techniques for array-based and pointer-intensive applications for reducing data cache leakage energy consumption. The idea is to let the compiler analyze the application code and insert instructions that turn off cache lines that keep variables not used by the current computation. This turning-off does not destroy contents of a cache line and waking up the cache line (when it is accessed later) does not incur much overhead. Due to inherent data locality in applications, we find that, at a given time, only a small portion of the data cache needs to be active; the remaining part can be placed into a leakage-saving mode (state); i.e., they can be turned off. Our experimental results indicate that the proposed compiler-based strategy reduces the cache energy consumption significantly. We also demonstrate how different compiler optimizations can increase the effectiveness of our strategy.