21618923
Meaning and precision of adaptive fuzzy systems with Gaussian-type membership functions
Fuzzy systems are unique in that they possess both linguistic input/output descriptions (the fuzzy if then rules) and numerical input/output descriptions (the input/output functions they implement). Adaptive fuzzy systems, also known as neural fuzzy systems, learn the functions they implement through training with numerical data. Precision--evaluated by the mean square error--has been the most important performance index. The linguistic meanings of the fuzzy if-then rules appear to be insignificant for adaptive fuzzy systems. We show that the linguistic meanings of system parameters can be used to set better initial values, thus reduce the mean square error. On the other hand, for adaptive fuzzy systems with Gaussian-type membership functions, there exist a trade-off between how meaningful the fuzzy if-then rules are and how precise the implemented function is. The fuzzy if-then rules may fail to provide a coarse description of the input/output function after training even when the mean square error is small. We propose a "mean square distance" that measures the meaning of the fuzzy system in terms of the discrepancy between the fuzzy if-then rules and the implemented numerical function. Performance of adaptive fuzzy systems are evaluated using both the mean square error (precision) and the mean square distance (meaning) in time series prediction experiments with Mackey Glass and Box Jenkins data. The effects of weight adaptation methods and varying Gaussian widths are studied. Adaptive fuzzy systems with Gaussian-type membership functions that perform well in precision (have small mean square error) may not have meaningful fuzzy if-then rules anymore.
15092090
More Golay sequences
Davis and Jedwab's construction of Golay sequences as Reed Muller codewords was believed to generate possibly all Golay sequences over Z/sub 2//sup h/ of length 2/sup m/. From exhaustive search, 1024 quaternary (h=2) Golay sequences of length 16 (m=4) are found which are not within Davis and Jedwab's construction. A table of 16 characteristic sequences is presented from which all 1024 Golay sequences can be reconstructed. The pairing information and the PAPR's of associated OFDM signals are given.
12311851
GABI-Kat SimpleSearch: an Arabidopsis thaliana T-DNA mutant database with detailed information for confirmed insertions
Insertional mutagenesis approaches, especially by T-DNA, play important roles in gene function studies of the model plant Arabidopsis thaliana. GABI-Kat SimpleSearch () is a Flanking Sequence Tag (FST)-based database for T-DNA insertion mutants generated by the GABI-Kat project. Currently, the database contains >108 000 mapped FSTs from ∼64 000 lines which cover 64% of all annotated A.thaliana protein-coding genes. The web interface allows searching for relevant insertions by gene code, keyword, line identifier, GenBank accession number of the FST, and also by BLAST. A graphic display of the genome region around the gene or the FST assists users to select insertion lines of their interests. About 3500 insertions were confirmed in the offspring of the plant from which the original FST was generated, and the seeds of these lines are available from the Nottingham Arabidopsis Stock Centre. The database now also contains additional information such as segregation data, gene-specific primers and confirmation sequences. This information not only helps users to evaluate the usefulness of the mutant lines, but also covers a big part of the molecular characterization of the insertion alleles.
1087466
Independence numbers of hypergraphs with sparse neighborhoods
Let H be a hypergraph with N vertices and average degree d. Suppose that the neighborhoods of H are sparse, then its independence number is at least cN(log d/d), where c > 0 is a constant. In particular, let integers r ≥ 3 and n ≥ 1 be fixed, and let H be r-uniform, triangle-free and linear, then its independence number is at least cN logn d/d for all sufficiently large d.
16081168
Sample dependence correction for order selection in fMRI analysis
Multivariate analysis methods such as independent component analysis (ICA) have been applied to the analysis of functional magnetic resonance imaging (fMRI) data to study the brain function. The selection of the proper number of signals of interest is an important step in the analysis to reduce the risk of over/underfilling. The inherent sample dependence in the spatial or temporal dimension of the fMRI data violates the assumption of independent and identically distributed (i.i.d.) samples and limits the usefulness of the practical formulations of information-theoretic order selection criteria. We propose a novel method using an entropy rate matching principle to mitigate the effects of such sample dependence in order selection. We perform order selection experiments on the simulated fMRI data and show that the incorporation of the proposed method significantly improves the accuracy of the order selection by different criteria. We also use the proposed method to estimate the number of latent sources in fMRI data acquired from multiple subjects performing a visuomotor paradigm. We show that the proposed method improves the order selection by alleviating the over-estimation due to the intrinsic smoothness and the effect of smooth preprocessing on the fMRI data
16004582
Formation Control for a Multiple Robotic System Using Adaptive Neural Network
Due to the limitations of sensors, each member of a decentralized system can only deal with local information respectively. A description of local relationship within formation pattern is proposed in this paper. Furthermore, a NN control approach with robust term is proposed to control individual motion. By using such individual control method, all robots will finally form a unique formation. Based on properties of such control strategy, we propose a modified artificial potential approach to realize obstacle avoidance.
7167027
Power and thermal effects of SRAM vs. latch-mux design styles and clock gating choices
This paper studies the impact on energy efficiency and thermal behavior of design style and clock-gating style in queue and array structures. These structures are major sources of power dissipation, and both design styles and various clock gating schemes can be found in modern, high-performance processors. Although some work in the circuits domain has explored these issues from a power perspective, thermal treatments are less common, and we are not aware of any work in the architecture domain. We study both SRAM and latch and multiplexer ("latch-mux") designs and their associated clock-gating options. Using circuit-level simulations of both design styles, we derive power-dissipation ratios which are then used in cycle-level power/performance/thermal simulations. We find that even though the "unconstrained" power of SRAM designs is always better than latch-mux designs, latch-mux designs dissipate less power in practice when a structure's average occupancy is low but access rate is high, especially when "stall gating" is used to minimize switching power. We also find that latch-mux designs with stall gating are especially promising from a thermal perspective, because they exhibit lower power density than SRAM designs. Overall, when combined with implementation and verification challenges for SRAMs, latch-mux designs with stall gating appear especially promising for designs with thermal constraints. This paper also shows the importance of considering the interaction between architectural and circuit design choices when performing early-stage design exploration.