Design, implementation and evaluation of broadband low noise amplifier (LNA) for radiometer

The two major applications of microwave remote sensors are radiometer and radar. Because of its importance and the nature of the application, much research has been made on the various aspects of the radar. This paper will focus on the various aspects of the radiometer from a design point of view and the Low Noise Amplifier will be designed and implemented. The paper is based on a study in radio Frequency Communications engineering and understanding of electronic and RF circuits. Some research study about the radiometer and practical implementation of Low Noise Amplifier for Radiometer will be the main focus of this paper. Basically the paper is divided into two parts. In the first part some background study about the radiometer will be carried out and commonly used types of radiometer will be discussed. In the second part LNA for the radiometer will be designed.

OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error

This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.

OFDM joint data detection and phase noise cancellation for constant modulus modulations

This correspondence proposes a new algorithm for the OFDM joint data detection and phase noise (PHN) cancellation for constant modulus modulations. We highlight that it is important to address the overfitting problem since this is a major detrimental factor impairing the joint detection process. In order to attack the overfitting problem we propose an iterative approach based on minimum mean square prediction error (MMSPE) subject to the constraint that the estimated data symbols have constant power. The proposed constrained MMSPE algorithm (C-MMSPE) significantly improves the performance of existing approaches with little extra complexity being imposed. Simulation results are also given to verify the proposed algorithm.

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

Green noise or green value? Measuring the effects of environmental certification on office values

This study investigates the price effects of environmental certification on commercial real estate assets. It is argued that there are likely to be three main drivers of price differences between certified and noncertified buildings. These are additional occupier benefits, lower holding costs for investors and a lower risk premium. Drawing upon the CoStar database of U.S. commercial real estate assets, hedonic regression analysis is used to measure the effect of certification on both rent and price. The results suggest that, compared to buildings in the same submarkets, eco-certified buildings have both a rental and sale price premium.

Classification of instability modes in a model of aluminium reduction cells with a uniform magnetic field

A unified view on the interfacial instability in a model of aluminium reduction cells in the presence of a uniform, vertical, background magnetic field is presented. The classification of instability modes is based on the asymptotic theory for high values of parameter β, which characterises the ratio of the Lorentz force based on the disturbance current, and gravity. It is shown that the spectrum of the travelling waves consists of two parts independent of the horizontal cross-section of the cell: highly unstable wall modes and stable or weakly unstable centre, or Sele’s modes. The wall modes with the disturbance of the interface being localised at the sidewalls of the cell dominate the dynamics of instability. Sele’s modes are characterised by a distributed disturbance over the whole horizontal extent of the cell. As β increases these modes are stabilized by the field.

Experimental model of the interfacial instability in aluminium reduction cells

A solution has been found to the long-standing problem of experimental modelling of the interfacial instability in aluminium reduction cells. The idea is to replace the electrolyte overlaying molten aluminium with a mesh of thin rods supplying current down directly into the liquid metal layer. This eliminates electrolysis altogether and all the problems associated with it, such as high temperature, chemical aggressiveness of media, products of electrolysis, the necessity for electrolyte renewal, high power demands, etc. The result is a room temperature, versatile laboratory model which simulates Sele-type, rolling pad interfacial instability. Our new, safe laboratory model enables detailed experimental investigations to test the existing theoretical models for the first time.

Multistep electrochemical reduction path of clusters [Os3(CO)10(α-diimine)]: comparison of electrochemical and photochemical Os-Os(α-diimine) bond cleavage

Electrochemical reduction of the triangular clusters [Os-3(CO)(10)(alpha-dimine)] (alpha-dimine = 2,2'-bipyridine (bpy), 2,2'-bipyrimidine (bpym)) and [Os-3(CO)(10)(mu-bpym) ReBr(CO)(3)] produces primarily the corresponding radical anions. Their stability is strongly determined by the pi acceptor ability of the reducible alpha-dimine ligand, which decreases in the order mu-bpym > bpym >> bpy. Along this series, increasing delocalisation of the odd electron density in the radical anion over the Os(alpha-dimine) chelate ring causes weakening of the axial (CO)(4)Os-Os(CO)(2)(alpha-dimine) bond and its facile cleavage for alpha-diimine = bpy. In contrast, the cluster radical anion is inherently stable for the bridging bpym ligand, the strongest pi-acceptor in the studied series. In the absence of the partial delocalisation of the unpaired electron over the Re( bpym) chelate bond, the Os-3-core of the radical anion remains intact only at low temperatures. Subsequent one-electron reduction of [Os-3(CO)(10)(bpym)](center dot-) at T = 223 K gives the open-triosmium core (= Os-3*) dianion, [Os-3*(CO)(10)(bpym)](2-). Its oxidation leads to the recovery of parent [Os-3(CO)(10)( bpym)]. At room temperature, [Os-3*( CO)(10)(bpym)](2-) is formed along a two-electron (ECE) reduction path. The chemical step (C) results in the formation of an open- core radical anion that is directly reducible at the cathodic potential of the parent cluster in the second electrochemical (E) step. In weakly coordinating tetrahydrofuran, [Os-3*(CO)(10)( bpym)](2-) rapidly attacks yet non- reduced parent cluster molecules, producing the relatively stable open- core dimer [Os-3*(CO)(10)(bpym)](2)(2-) featuring two open- triangle cluster moieties connected with an ( bpym) Os - Os( bpym) bond. In butyronitrile, [Os-3*( CO)(10)(bpym)](2-) is stabilised by the solvent and the dimer [Os-3*(CO)(10)(bpym)](2)(2-) is then mainly formed by reoxidation of the dianion on reverse potential scan. The more reactive cluster [Os-3(CO)(10)(bpy)] follows the same reduction path, as supported by spectroelectrochemical results and additional valuable evidence obtained from cyclic voltammetric scans. The ultimate process in the reduction mechanism is fragmentation of the cluster core triggered by the reduction of the dimer [Os-3*(CO)(10)(alpha- diimine)](2)(2-). The products formed are [Os-2(CO)(8)](2-) and {Os(CO)(2)(alpha- diimine)}(2). The latter dinuclear fragments constitute a linear polymeric chain [Os( CO)(2)(alpha-dimine)] n that is further reducible at the alpha-dimine ligands. For alpha-dimine = bpy, the charged polymer is capable of reducing carbon dioxide. The electrochemical opening of the triosmium core in the [Os-3( CO)(10)(alpha-dimine)] clusters exhibits several common features with their photochemistry. The same Os-alpha-dimine bond dissociates in both cases but the intimate mechanisms are different.

Modified level set method with Canny operator for image noise removal

The level set method is commonly used to address image noise removal. Existing studies concentrate mainly on determining the speed function of the evolution equation. Based on the idea of a Canny operator, this letter introduces a new method of controlling the level set evolution, in which the edge strength is taken into account in choosing curvature flows for the speed function and the normal to edge direction is used to orient the diffusion of the moving interface. The addition of an energy term to penalize the irregularity allows for better preservation of local edge information. In contrast with previous Canny-based level set methods that usually adopt a two-stage framework, the proposed algorithm can execute all the above operations in one process during noise removal.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Neurofuzzy control using Kalman filtering state feedback with coloured noise for unknown non-linear processes

This paper presents a controller design scheme for a priori unknown non-linear dynamical processes that are identified via an operating point neurofuzzy system from process data. Based on a neurofuzzy design and model construction algorithm (NeuDec) for a non-linear dynamical process, a neurofuzzy state-space model of controllable form is initially constructed. The control scheme based on closed-loop pole assignment is then utilized to ensure the time invariance and linearization of the state equations so that the system stability can be guaranteed under some mild assumptions, even in the presence of modelling error. The proposed approach requires a known state vector for the application of pole assignment state feedback. For this purpose, a generalized Kalman filtering algorithm with coloured noise is developed on the basis of the neurofuzzy state-space model to obtain an optimal state vector estimation. The derived controller is applied in typical output tracking problems by minimizing the tracking error. Simulation examples are included to demonstrate the operation and effectiveness of the new approach.

Algorithmic statistical analysis of electrophysiological data for the investigation of structure-activity relationship in single neurons

We are developing computational tools supporting the detailed analysis of the dependence of neural electrophysiological response on dendritic morphology. We approach this problem by combining simulations of faithful models of neurons (experimental real life morphological data with known models of channel kinetics) with algorithmic extraction of morphological and physiological parameters and statistical analysis. In this paper, we present the novel method for an automatic recognition of spike trains in voltage traces, which eliminates the need for human intervention. This enables classification of waveforms with consistent criteria across all the analyzed traces and so it amounts to reduction of the noise in the data. This method allows for an automatic extraction of relevant physiological parameters necessary for further statistical analysis. In order to illustrate the usefulness of this procedure to analyze voltage traces, we characterized the influence of the somatic current injection level on several electrophysiological parameters in a set of modeled neurons. This application suggests that such an algorithmic processing of physiological data extracts parameters in a suitable form for further investigation of structure-activity relationship in single neurons.