767826
The Spectral Independent Components of Natural Scenes
We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was able to find basis functions that had a broadband spectrum similar to natural daylight, as well as basis functions that coincided with the human cone sensitivity response functions. When applied to small image patches, the algorithm found homogeneous basis functions, achromatic basis functions, and basis functions with overall chromatic variation along lines in color space. Our findings suggest that ICAm ay be used to reveal the structure of color information in natural images.
207739442
Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources
An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly to separate mixed signals with sub- and supergaussian source distributions. This was achieved by using a simple type of learning rule first derived by Girolami (1997) by choosing negentropy as a projection pursuit index. Parameterized probability distributions that have sub- and supergaussian regimes were used to derive a general learning rule that preserves the simple architecture proposed by Bell and Sejnowski (1995), is optimized using the natural gradient by Amari (1998), and uses the stability analysis of Cardoso and Laheld (1996) to switch between sub- and supergaussian regimes. We demonstrate that the extended infomax algorithm is able to separate 20 sources with a variety of source distributions easily. Applied to high-dimensional data from electroencephalographic recordings, it is effective at separating artifacts such as eye blinks and line noise from weaker electrical signals that arise from sources in the brain.
6741849
Blind Separation of Delayed and Convolved Sources
We address the difficult problem of separating multiple speakers with multiple microphones in a real room. We combine the work of Torkkola and Amari, Cichocki and Yang, to give Natural Gradient information maximisation rules for recurrent (IIR) networks, blindly adjusting delays, separating and deconvolving mixed signals. While they work well on simulated data, these rules fail in real rooms which usually involve non-minimum phase transfer functions, not-invertible using stable IIR filters. An approach that sidesteps this problem is to perform infomax on a feedforward architecture in the frequency domain (Lambert 1996). We demonstrate real-room separation of two natural signals using this approach.
8163714
Scaling Laws in Natural Scenes and the Inference of 3D Shape
This paper explores the statistical relationship between natural images and their underlying range (depth) images. We look at how this relationship changes over scale, and how this information can be used to enhance low resolution range data using a full resolution intensity image. Based on our findings, we propose an extension to an existing technique known as shape recipes [3], and the success of the two methods are compared using images and laser scans of real scenes. Our extension is shown to provide a two-fold improvement over the current method. Furthermore, we demonstrate that ideal linear shape-from-shading filters, when learned from natural scenes, may derive even more strength from shadow cues than from the traditional linear-Lambertian shading cues.
39601893
Smoothing parameter selection for smoothing splines: a simulation study
Smoothing splines are a popular method for performing nonparametric regression. Most important in the implementation of this method is the choice of the smoothing parameter. This article provides a simulation study of several smoothing parameter selection methods, including two so-called risk estimation methods. To the best of the author's knowledge, the empirical performances of these two risk estimation methods have never been reported in the literature. Empirical conclusions from and recommendations based on the simulation results will be provided. One noteworthy empirical observation is that the popular method, generalized cross-validation, was outperformed by another method, an improved Akaike Information criterion, that shares the same assumptions and computational complexity.
7135959
On original generation of structure in legal documents
This position paper advocates a vision in the development of automated legal reasoning and presents evidence supporting the plausibility of that vision. The paper observes that original creation of documents of legal import in either fully formal or semistructured form offers the prospect of greatly reducing the cost and expanding the scope of knowledge engineering for legal reasoning. This, it is claimed, is most likely to be achieved via formalization of various sublanguages of legal discourse. SeaSpeak is an example of such a sublanguage and it appears to be amenable to full formalization. Short of that, much can be done with partial formalization and semistructured documents. The paper presents a tabular format for message expression, motivated by a formal agent communication language.
7698976
Segmenting Images Corrupted by Correlated Noise
Image segmentation is fundamental to many image analysis problems. It aims to partition a digital image into a set of nonoverlapping homogeneous regions. The main contribution of this paper is the development of a new segmentation procedure which is designed to segment images corrupted by correlated noise. This new segmentation procedure is based on Rissanen's minimum description length (MDL) principle and consists of two components: 1) an MDL-based criterion in which the "best" segmentation is defined as its minimizer; and 2) a merging algorithm which attempts to locate this minimizer. The performance of this procedure is illustrated via a simulation study, with promising results.
206754645
Statistical performance guarantees in large-scale cross-path packet switch
In this paper, we develop a general framework for a novel switch architecture, the cross-path switch, to provide persession statistical quality of service (QoS) guarantees. With characterizing the service each session receives by service curves, we derive a set of statistical bounds on the delay, backlog, and departure processes at the switch on a per-session manner using exponential bounded burstiness processes as source session traffic models. These bounds show that the service guarantees offered by the cross-path switch depend on the way of token assignment in the central stage of the switch. To provide better performance guarantees,we determine the criteria for designing a token assignment algorithm for the cross-path switch. Also, we quantify the service guaranteed by the cross-path switch with the central stage implemented in optical domain, which is important for the provision of QoS guarantees to each session in semioptical networks.