Learning Automata from Ordered Examples

Connectionist learning models have had considerable empirical success, but it is hard to characterize exactly what they learn. The learning of finite-state languages (FSL) from example strings is a domain which has been extensively studied and might provide an opportunity to help understand connectionist learning. A major problem is that traditional FSL learning assumes the storage of all examples and thus violates connectionist principles. This paper presents a provably correct algorithm for inferring any minimum-state deterministic finite-state automata (FSA) from a complete ordered sample using limited total storage and without storing example strings. The algorithm is an iterative strategy that uses at each stage a current encoding of the data considered so far, and one single sample string. One of the crucial advantages of our algorithm is that the total amount of space used in the course of learning for encoding any finite prefix of the sample is polynomial in the size of the inferred minimum state deterministic FSA. The algorithm is also relatively efficient in time and has been implemented. More importantly, there is a connectionist version of the algorithm that preserves these properties. The connectionist version requires much more structure than the usual models and has been implemented using the Rochester Connectionist Simulator. We also show that no machine with finite working storage can iteratively identify the FSL from arbitrary presentations.     

Performance analysis of a class of transient detection algorithms-aunified framework

The detection of short-duration nonstationary signals, which are commonly referred to as transients, is often performed in the time-frequency-transform domain. An analytical framework within which the performance of different detectors based on linear transforms can be easily compared, for different classes of signals, is developed. A given class of transients is modeled as a signal existing in a linear subspace, plus a mismatch signal. Closed-form expressions are derived for the best and the worst detection performance for all possible transients in a given class. Using this framework, the performance of detectors based on the Gabor transform and on the short-time Fourier transform is evaluated and compared     

Effects of fiber from tropical corn and forage sorghum silages on intake, digestion, and performance of lactating dairy cows

Tropical corn silage was compared with sorghum silage as a basal forage in the diets of high producing dairy cows. Sorghum and tropical corn silages were each included in place of ground corn at incremental concentrations in the experimental diets. Eight separate diets were fed, four diets containing each silage ranging in forage neutral detergent fiber (NDF) from approximately 25 to 31% and ranging in total NDF from approximately 41 to 45%. Diets were arranged in a 2 x 4 factorial design and were fed to lactating cows (n = 24; pretrial mean milk production = 39 kg/d; body weight = 656 kg; and days in milk = 81). As concentrations of dietary NDF increased, intake and milk production decreased linearly. The impact of dietary NDF on intake was greater for diets based on tropical corn silage than for diets based on sorghum silage. Energy intake and milk production were reduced, but cows consumed more fiber when challenged with higher dietary concentrations of fiber. The in vitro rate and extent of digestion of dietary samples were correlated with intake response. The rate of in vitro fiber digestion was slower for samples that contained tropical corn silage than for samples that contained sorghum silage. In vivo digestibility measurements were influenced by intake and dietary composition. Results of this trial indicated that sorghum silage can have equal or slightly greater nutritional value than tropical corn silage when these forages are fed at equal concentrations of dietary fiber.     

Estimation of frequency in the presence of nonrandom interference

This paper develops a method of error analysis for Fourier transform-based sinusoidal frequency estimation in the presence of nonrandom interferences. A general error formula is derived and then specialized to the cases of additive and multiplicative interferences. Approximate error formulas are derived for the case of additive polynomial-phase interference. Finally, an application to error analysis in estimating the parameters of multiple polynomial-phase signals is discussed in detail     

A backstepping controller for path‐tracking of an underactuated autonomous airship

In this paper we propose a nonlinear control approach for the path‐tracking of an autonomous underactuated airship. A backstepping controller is designed from the airship nonlinear dynamic model including wind disturbances, and further enhanced to consider actuators saturation. Control implementation issues related to airship underactuation are also addressed, namely control allocation and an attitude reference shaping to obtain a faster error correction with smoother input requests. The results obtained demonstrate the capacity of an underactuated unmanned airship to execute a realistic mission including vertical take‐off and landing, stabilization and path‐tracking, in the presence of wind disturbances, with a single robust control law. Copyright © 2008 John Wiley & Sons, Ltd.     

Top-down proteomic analysis by MALDI-TOF profiling: Concentration-independent biomarkers

Although numerous protein biomarkers have been correlated with advanced disease states, no new clinical assays have been developed. Goals often anticipate disease-specific protein changes that exceed values among healthy individuals, a property common to acute phase reactants. This review considers somewhat different approaches. It focuses on intact protein isoform ratios that present a biomarker without change in the total concentration of the protein. These will seldom be detected by peptide level analysis or by most antibody-based assays. For example, application of an inexpensive method to large sample groups resulted in observation of several polymorphisms, including the first structural polymorphism of apolipoprotein C1. Isoform distribution of this protein was altered and was eventually linked to increased obesity. Numerous other protein isoforms included C- and N-terminal proteolysis, changes of glycoisoform ratios and certain types of sulfhydryl oxidation. While many of these gave excellent statistical correlation with advanced disease, clinical utility was not apparent. More important may be that protein isoform ratios were very stable in each individual. Diagnosis by longitudinal analysis of the same individual might increase sensitivity of protein biomarkers by 20-fold or more. Protein changes that exceed the range of values found among healthy individuals may be uncommon.