Survey of learning control systems for space vehicle applications.
On-line and off-line self-organizing control systems for space vehicle application
CONTROL SYSTEM↗
SEARCH · Engineering Papers
Results for “self-organization”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Hysteresis and macromolecular memory
Hysteresis and macromolecular memory, and memory device requirements as part of cybernetic self-organizing systems
MACROMOLECULE↗
Computers formed by the problems rather than problems deformed by the computers.
Description of an approach to computer programming which tries to minimize the time required for retranslation from the computer language into the language of the original process. A notion of a programmable network is introduced which allows the abstract machines that are a model of the processes in the user's mind to be put into a rigorous and simple form. Each process is then modeled as a particular finite-state machine, a circulating page loose system being employed as an architecture for implementing these finite-state machines. An experiment is discussed in which the use of abstract machines as a language for modeling processes, in conjunction with the use of a self-organizing computer, decreases user effort, eliminates the need for compilation, facilitates debugging, and decreases computer time.
Schaffner, M. R.↗
Effect of various features on the life cycle cost of the timing/synchronization subsystem of the DCS digital communications network
The effect on the life cycle cost of the timing subsystem was examined, when these optional features were included in various combinations. The features included mutual control, directed control, double-ended reference links, independence of clock error measurement and correction, phase reference combining, self-organization, smoothing for link and nodal dropouts, unequal reference weightings, and a master in a mutual control network. An overall design of a microprocessor-based timing subsystem was formulated. The microprocessor (8080) implements the digital filter portion of a digital phase locked loop, as well as other control functions such as organization of the network through communication with processors at neighboring nodes.
Kimsey, D. B.↗
CLASSY: An adaptive maximum likelihood clustering algorithm
The CLASSY clustering method alternates maximum likelihood iterative techniques for estimating the parameters of a mixture distribution with an adaptive procedure for splitting, combining, and eliminating the resultant components of the mixture. The adaptive procedure is based on maximizing the fit of a mixture of multivariate normal distributions to the observed data using its first through fourth central moments. It generates estimates of the number of multivariate normal components in the mixture as well as the proportion, mean vector, and covariance matrix for each component. The basic mathematical model for CLASSY and the actual operation of the algorithm as currently implemented are described. Results of applying CLASSY to real and simulated LANDSAT data are presented and compared with those generated by the iterative self-organizing clustering system algorithm on the same data sets.
Lennington, R. K.↗
An evaluation of ISOCLS and CLASSY clustering algorithms for forest classification in northern Idaho
Both the iterative self-organizing clustering system (ISOCLS) and the CLASSY algorithms were applied to forest and nonforest classes for one 1:24,000 quadrangle map of northern Idaho and the classification and mapping accuracies were evaluated with 1:30,000 color infrared aerial photography. Confusion matrices for the two clustering algorithms were generated and studied to determine which is most applicable to forest and rangeland inventories in future projects. In an unsupervised mode, ISOCLS requires many trial-and-error runs to find the proper parameters to separate desired information classes. CLASSY tells more in a single run concerning the classes that can be separated, shows more promise for forest stratification than ISOCLS, and shows more promise for consistency. One major drawback to CLASSY is that important forest and range classes that are smaller than a minimum cluster size will be combined with other classes. The algorithm requires so much computer storage that only data sets as small as a quadrangle can be used at one time.
Werth, L. F.↗
Intelligent signal analysis and recognition
Progress in the research and development of self-organizing database system that can support the identification and characterization of signals in an RF environment is described. As the radio frequency spectrum becomes more crowded, there are a number of situations that require a characterization of the RF environment. This database system is designed to be practical in applications where communications and other instruments encounter a time varying and complex RF environment. The primary application of this system is the guidance and control of NASA's SETI Microwave Observing Project. Other possible applications include selection of telemety bands for communication with spacecraft, and the scheduling of antenna for radio astronomy are two examples where characterization of the RF environment is required. In these applications, the RF environment is constantly changing, and even experienced operators cannot quickly identify the multitude of signals that can be encountered. Some of these signals are repetitive, others appear to occur sporadically.
Levinson, Robert↗
Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing
Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.
Farhat, Nabil H.↗
Planetary environments and the conditions of life
Geophysical models of the first 600 Ma ofthe earth's history following accretion and core formation point to a period of great environmental disequilibrium. In such an environment, the passage of energy from the earth's interior and from the sun through gas-liquid-solid domains and their boundaries with each other generated a dynamically interacting, complex hierarchy of self-organized structures ranging from bubbles at the sea-air interface to tectonic plates. The ability of a planet to produce such a hierarchy is speculated to be a prerequisite to the origin and sustenance of life. The application of this criterion to Mars argues against the origin of Martian life.
Chang, S.↗
Oligomerization of deoxynucleoside-biphosphate dimers - Template and linkage specificity
The oligomerization of the activated 3-prime-5-prime pyrophosphate-linked dimer, pdAppdAp, is presently noted to be selectively favored by a poly(U) template over the 3-prime-3-prime and 5-prime-5-prime linked dimers. Both overall yields and the production of the longest oligomers were markedly stimulated by poly(U)'s presence; in its absence, the 5-prime-5-prime linked dimer became the most reactive, yielding chains of the order of 60 monomer-unit lengths. Remarkable self-organization properties are noted for the 5-prime-5-prime dimer of pdAp.
Visscher, J.↗
Terminal attractors in neural networks
A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.
Zak, Michail↗
Integrated communication and information fabric for space applications
The results of preliminary research into infrastructures for integrated communication and information fabrics, which can meet the needs of space applications of the future, are presented. Technologies that foster scaleability and adaptability and support self-organizing mechanisms are needed to effectively integrate the working fabric of a large-scale distributed system. A multigrid network architecture that uses a completely distributed packet-routing scheme is derived. The first part of the paper introduces a simple model of a communication and information system for space applications, the second discusses the known limitations of the large-scale future communication and information systems, and the third part describes the results of preliminary research in this area. It is expected that this technology will result in inexpensive networks utilizing multigigabit-per-second data links.
Maitan, J.↗
Observation of seeded second harmonic generation in bulk germanosilicate fiber preforms
Simultaneous irradiation of a bulk fiber preform with molar concentrations of 3 pct Ge and 0.5 pct P doped silica core region resulted in self-organized second harmonic generation with an effective chi(2) of about 1.2 x 10 to the -16th m/V. The experiments revealed that the bulk preform requires the same critical IR intensity (10 GW/sq cm) as the drawn fibers to prepare. Attempts to self-prepare the preform field, indicating that self-preparation in fibers is most likely initiated by second harmonic generation associated with the core-cladding interface.
Lawandy, N. M.↗
Cosmic instability from radiation pressure
The Cosmic Background Explorer has recently confirmed the blackbody character of the microwave background to high accuracy (Mather et al., 1990), and will have the capability to detect other cosmic backgrounds throughout the infrared. A detection of cosmic background radiation dating from the pregalactic era would have important consequences for theories of cosmic structure. During the creation of such a background the pressure of the radiation itself causes an instability which leads inevitably to the growth of large-scale structure in the matter distribution. In contrast to conventional gravitational-instability models, the statistical properties of this structure are determined primarily by the self-organizing dynamics of the instability rather than details of cosmological initial conditions. The behavior of the instability is described here.
Hogan, Craig J.↗
Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim++ Lens Sample
In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3x2pt cosmology analysis. The 3x2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection (Balrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O($10^8$) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the $n(z)$ uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. This analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.
Giannini, G. [Chicago U., Astron. Astrophys. Ctr.;↗
Dark Energy Survey Year 6 Results: Redshift Calibration of the Weak Lensing Source Galaxies
Determining the distribution of redshifts for galaxies in wide-field photometric surveys is essential for robust cosmological studies of weak gravitational lensing. We present the methodology, calibrated redshift distributions, and uncertainties of the final Dark Energy Survey Year 6 (Y6) weak lensing galaxy data, divided into four redshift bins centered at $\langle z \rangle = [0.414, 0.538, 0.846, 1.157]$. We combine independent information from two methods on the full shape of redshift distributions: optical and near-infrared photometry within an improved Self-Organizing Map $p(z)$ (SOMPZ) framework, and cross-correlations with spectroscopic galaxy clustering measurements (WZ), which we demonstrate to be consistent both in terms of the redshift calibration itself and in terms of resulting cosmological constraints within 0.1$σ$. We describe the process used to produce an ensemble of redshift distributions that account for several known sources of uncertainty. Among these, imperfection in the calibration sample due to the lack of faint, representative spectra is the dominant factor. The final uncertainty on mean redshift in each bin is $σ_{\langle z\rangle} = [0.012, 0.008,0.009, 0.024]$. We ensure the robustness of the redshift distributions by leveraging new image simulations and a cross-check with galaxy shape information via the shear ratio (SR) method.
Yin, B. [Duke U.] (ORCID:0009000656049980)↗
The Power of DESI for Photometric Redshift Calibration: A Case Study with KiDS-1000
Accurate redshift estimates are a critical requirement for weak lensing surveys and one of the main uncertainties in constraints on dark energy and large-scale cosmic structure. In this paper, we study the potential to calibrate photometric redshift (photo-z) distributions for gravitational lensing using the Dark Energy Spectroscopic Instrument (DESI). Since beginning its science operations in 2021, DESI has collected more than 50 million redshifts, adding about one million monthly. In addition to its large-scale structure samples, DESI has also acquired over 256k high-quality spectroscopic redshifts (spec-zs) in the COSMOS and XMM and VVDS fields. This is already a factor of 3 larger than previous spec-z calibration compilations in these two regions. Here, we explore calibrating photo-zs for the subset of KiDS-1000 galaxies that fall into joint self-organizing map (SOM) cells overlapping the DESI COSMOS footprint using the DESI COSMOS observations. Estimating the redshift distribution in KiDS-1000 with the new DESI data, we find broad consistency with previously published results while also detecting differences in the mean redshift in some tomographic bins with an average shifts of Delta Mean(z) = -0.028 in the mean and Delta Median(z) = +0.011 in the median across tomographic bins. However, we also find that incompleteness per SOM cell, i.e., groups of galaxies with similar colors and magnitudes, can modify n(z) distributions. Finally, we comment on the fact that larger photometric catalogs, aligned with the DESI COSMOS and DESI XMM and VVDS footprints, would be needed to fully exploit the DESI dataset and would extend the coverage to nearly eight times the area of existing 9-band photometry.
Blanco, Diana [UC, Santa Cruz; UC, Santa Cruz, Ins↗
Microscopic Imprints of Learned Solutions in Tunable Networks
In physical networks trained using supervised learning, physical parameters are adjusted to produce desired responses to inputs. An example is an electrical contrastive local learning network of nodes connected by edges that adjust their conductances during training. When an edge conductance changes, it upsets the current balance of every node. In response, physics adjusts the node voltages to minimize the dissipated power. Learning in these systems is therefore a coupled double-optimization process, in which the network descends both a cost landscape in the high-dimensional space of edge conductances and a physical landscape—the power dissipation—in the high-dimensional space of node voltages. Because of this coupling, the physical landscape of a trained network contains information about the learned task. Here, we derive a structure-function relation for trained tunable networks and demonstrate that all the physical information relevant to the trained input-output relation can be captured by a tuning susceptibility, an experimentally measurable quantity. We supplement our theoretical results with simulations to show that the tuning susceptibility is correlated with functional importance and that we can extract physical insight into how the system performs the task from the conductances of highly susceptible edges. Our analysis is general and can be applied directly to mechanical networks, such as networks trained for protein-inspired function such as allostery.
36 MATERIALS SCIENCE↗