Belief Refinement Approaches to Communication and Inference Problems

This dissertation considers a problem where a single agent or a group of agents aim to estimate/learn unknown (possibly time-varying) parameters of interest despite making noisy observations. The agents take a Bayesian-like approach by maintaining a posterior probability distribution or “belief" over a parameter space conditioned on past observations. The agents aim to iteratively refine their belief over the parameter space as new information is acquired from their private observations or through collaboration with other agents. In particular, the agents aim to ensure that sufficient belief is assigned in neighborhoods centered around the true parameter with high probability or “reliability". In the context of communication problems considered in this dissertation, the agents may be active, i.e., agents may additionally take actions which provide new observations. Furthermore, agents may employ an adaptive strategy, i.e., using their past actions and the resulting observations, agents can adaptively choose actions to control the concentration of the belief. When the agents are active, we propose and analyze adaptive belief refinement approaches to obtain belief concentration on the unknown parameter with high reliability. In a different context, namely that of decentralized inference, we consider passive agents. Here, agents face an additional challenge due to the statistical insufficiency of their private observations to learn the unknown parameter. While individual agents’ observations are not informative enough, we assume that the agents’ observations are collectively informative to learn the unknown parameter. Here, we propose and analyze decentralized belief refining strategies to collaboratively obtain belief concentration on the unknown parameter. In the first part of this dissertation, we consider active strategies that are extensions of the posterior matching strategy (PM) introduced by Horstein, which is a generalization of the well-known binary search algorithm. We propose and analyze PM based strategies in the context of modern communication systems, namely the problem of establishing initial access in mm-Wave communication and spectrum sensing for Cognitive Radio. We propose and analyze channel coding strategies for real-time streaming and control applications. The second part of the dissertation investigates the belief refinement approaches for decentralized learning. In particular, it focusing on developing and analyzing a decentralized learning rule for statistical hypothesis testing and its application to decentralized machine learning

Automatic Grammar Augmentation for Robust Voice Command Recognition

This paper proposes a novel pipeline for automatic grammar augmentation that provides a significant improvement in the voice command recognition accuracy for systems with small footprint acoustic model (AM). The improvement is achieved by augmenting the user-defined voice command set, also called grammar set, with alternate grammar expressions. For a given grammar set, a set of potential grammar expressions (candidate set) for augmentation is constructed from an AM-specific statistical pronunciation dictionary that captures the consistent patterns and errors in the decoding of AM induced by variations in pronunciation, pitch, tempo, accent, ambiguous spellings, and noise conditions. Using this candidate set, greedy optimization based and cross-entropy-method (CEM) based algorithms are considered to search for an augmented grammar set with improved recognition accuracy utilizing a command-specific dataset. Our experiments show that the proposed pipeline along with algorithms considered in this paper significantly reduce the mis-detection and mis-classification rate without increasing the false-alarm rate. Experiments also demonstrate the consistent superior performance of CEM method over greedy-based algorithms

A CURRENT BILL STATISTICAL VALUES TRACKING DEVICE USING RELAY CIRCUITS

Thinking about all pro & cons of traditional & automatic metering system, this research proposes a radio ARM- based automatic meter studying & control system. The wireless media made the exchange of knowledge fast, guaranteed & better. You will find another kind of customers also, that not just continues electricity is matter but additionally about quality of power can also be matter. The primary problem of calculating analog quantities for example current & current is solved by utilizing Power transformer (PT) & Current Transformer (CT). There is numerous micro-processor based digital power meters can be found in laboratory & in market. They are essentially bulky in dimensions & getting limited abilities. Relay Control Unit can be used to turning off the electrical power once the signal from AES because deadline has ended. Electricity will resume instantly with the aid of protective relay wired in series with breaker control circuit, therefore the breaker might be controlled. Among many versions of Visual Fundamental which exist on the market, typically the most popular one but still broadly used by lots of VB programmers is Visual Fundamental 6. ARM executes the majority of the instruction in just one cycle while 8051 micro controller takes several cycles in the majority of the instruction except register transfer. This research adopts LPC2148 ARM Processor for AES System. ARM based embedded product is getting simple functioning rival their counterparts. So computer software development can be achieved in popular C Language

Trimesic acid on Cu in ethanol: Potential-dependent transition from 2-D adsorbate to 3-D metal-organic framework

We report the potential-dependent interactions of trimesic acid with Cu surfaces in EtOH. CV experiments and electrochemical surface-enhanced Raman spectroscopy show the presence of an adsorbed trimesic acid layer on Cu at potentials lower than 0 V vs Cu. The BTC coverage increases as the potential increases, reaching a maximum at 0 V. Based on molecular dynamics simulations, we report adsorption geometries and possible structures of the organic adlayer. We find that, depending on the crystal facet, trimesic acid adsorbs either flat or with one or two of the carboxyl groups facing the metal surface. At higher coverages, a multi-layer forms that is composed mostly of flat-lying trimesic acid molecules. Increasing the potential beyond 0 V activates the Cu-adsorbate interface in such a way that under oxidation of Cu to Cu2 +, a 3-D metal-organic framework forms directly on the electrode surface.PS gratefully acknowledges the Max Planck Graduate Center and the Studienstiftung des deutschen Volkes for the funding. KFD gratefully acknowledges the generous funding through the Emmy Noether program of the Deutsche Forschungsgemeinschaft (DO 1691/1-1)