Although generation of correlated Rayleigh fading envelopes has been intensively considered in the literature, all conventional methods have their own shortcomings, which seriously impede their applicability. A very g...
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Although generation of correlated Rayleigh fading envelopes has been intensively considered in the literature, all conventional methods have their own shortcomings, which seriously impede their applicability. A very general, straightforward algorithm for the generation of an arbitrary number of Rayleigh envelopes with any desired, equal or unequal power, in wireless channels either with or without Doppler frequency shifts, is proposed. The proposed algorithm can be applied to the case of spatial correlation, such as with multiple antennas in multiple-input multiple-output (MIMO) systems, or spectral correlation between the random processes like in orthogonal frequency-division multiplexing (OFDM) systems. It can also be used for generating correlated Rayleigh fading envelopes in either discrete-time instants or a real-time scenario. Besides being more generalized, our proposed algorithm is more precise, while overcoming all shortcomings of the conventional methods.
Recent psychophysical studies suggest that human listeners do not segregate concurrent sounds by grouping frequency regions that have a common interaural time difference (ITD). However, such an approach is adopted by ...
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Recent psychophysical studies suggest that human listeners do not segregate concurrent sounds by grouping frequency regions that have a common interaural time difference (ITD). However, such an approach is adopted by most computational auditory scene analysis (CASA) systems that use binaural cues. Here, we propose a CASA system that separates a target speech signal from a noise interferer, but does not require the ITD of the two sources to be consistent across frequency. We compare the CASA system with human performance on the same task, in which the speech reception threshold (SRT) is measured for speech and noise stimuli which have consistent or inconsistent ITDs in different frequency bands. The CASA system is shown to be in qualitative agreement with human performance.
In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in X-ray image sequences. Different with traditional DSA image registration processes, in our ...
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We report a silicon/germanium saturable Bragg reflector, compatible with CMOS processing. Its sub-picosecond recovery time enables a C-band spanning mode-locked Er-Yb:glass laser at 1540 nm, generating 220 fs pulses. ...
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This paper shows the design, implementation and evaluation of an auditory user interface for a file-manager application. The intention for building this prototype was to prove concepts developed to support user interf...
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ISBN:
(纸本)9788474023183
This paper shows the design, implementation and evaluation of an auditory user interface for a file-manager application. The intention for building this prototype was to prove concepts developed to support user interface designers with design patterns in order to create robust and efficient auditory displays. The paper describes the motivation for introducing a mode-independent meta domain in which the design patterns were defined to overcome the problem of translating mainly visual concepts to the auditory domain. The prototype was implemented using the I EM Ambisonics libraries for Pure Data to produce high quality binaural audio rendering and used headtracking and a joystick as the main interaction devices.
In spectral representations of discrete functions, the main optimization goal is to reduce the number of non-zero spectral coefficients of the function that is represented as a linear combination of a set of basis fun...
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In spectral representations of discrete functions, the main optimization goal is to reduce the number of non-zero spectral coefficients of the function that is represented as a linear combination of a set of basis functions. Fourier transform for matrix-valued functions provides a deterministic way to redistribute the complexity of a spectral representation into a small set of matrix-valued coefficients.
While feature selection is very difficult for high dimensional, unstructured data such as face image, it may be much easier to do if the data can be faithfully transformed into lower dimensional space. In this paper, ...
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Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet. A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobj...
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Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet. A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobjective genetic algorithm, after the related work is reviewed. The contribution lies on that the selection process of such routing is treated with multiobjective optimization. Different quality criterions in IP network are taken into account for multicast communications. A set of routing trees is generated to approximate the Pareto front of multicast problem. Multiple trees can be selected from the final set of nondominated solutions, and applied to obtain a good overall link cost and balance traffic distribution according to some simulation results.
Fingerprint recognition is an interesting subject in biometric. As theirs pattern complication, classifying and identifying them with uncertainty are critical problems in pattern recognition. Fingerprint feature extra...
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Fingerprint recognition is an interesting subject in biometric. As theirs pattern complication, classifying and identifying them with uncertainty are critical problems in pattern recognition. Fingerprint feature extraction is most important process for identifying them as well. In this paper besides of using effective methods for extraction of features a five layer feed forward Fuzzy Neural Network composed by fuzzy neurons and its associated learning algorithm has been introduced for classification of shifted and distorted patterns. For generating input patterns to feed the matching network, the algorithm extracts singular points and minutiae of each pattern by using the optimum segmentation and recovering methods. The pattern of these features which are extracted of different shapes of fingerprints, let call it "feature map", will be encoded and applied to the intelligent classifier, The network first fuzzifies the entry then computes its similarities to all of the learned patterns, finally the network select the learned pattern of highest similarity and return its specific class illustrator of a person, as a non fuzzy output. We applied the database of almost 100 fingerprint acquired from ten people contain two types of minutiae and three types of singular points. The learning speed and matching capability are improved by using the feature coding method. Necessary time for feature extraction and classifying of 100 different fingerprints with 220*176 dimensions and 315 dpi resolutions is less than 20 second. Also necessary space for storing image bank becomes small, up to 2.54Kbyte per each feature map. This FNN is a classifying system with supervised learning algorithm.
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