Joint Power Amplifiers and I/Q Modulator Impairments Modelling and Compensation for LTE Transmitters Using Artificial Neural Networks

This work introduces joint power amplifier (PA) and I/Q modulator modelling and compensation for LongTerm Evolution (LTE) transmitters using artificial neural networks (ANNs). The proposed solution util-izes a powerful nonlinear autoregressive with exogenous inputs (NARX) ANN architecture, which yieldsnoticeable results for high peak to average power ratio (PAPR) LTE signals. Given the ANNs learning capa-bilities, this one-step solution, which includes the mitigation of both PA nonlinearity and I/Q modulatorimpairments, is both accurate and adaptable

Joint compensation of IQ-imbalance and carrier phase sychronization errors in communication receivers

This work addresses the joint compensation of IQimbalances and carrier phase synchronization errors of zero- IF receivers. The compensation scheme based on blind-source separation which provides simple yet potent means to jointly compensate for these errors independent of modulation format and constellation size used. The low-complexity of the algorithm makes it a suitable option for real-time deployment as well as practical for integration into monolithic receiver designs.

Adaptive compensation of analog front-end I/Q mismatches in digital receivers

I and Q Channel phase and gain misniatches are of great concern in communications receiver design. In this paper we analyse the effects of I and Q channel mismatches and propose a low-complexity blind adaptive algorithm to minimize this problem. The proposed solution consists of two, 2-tap adaptive filters, arranged in Adaptive Noise Canceller (ANC) set-up, with the output of one cross-fed to the input of the other. The system works as a de-correlator eliminating I and Q mismatch errors.

Analysis and compensation of RF impairments for next generation multimode GNSS receivers

Global navigation satellite system (GNSS) receivers require solutions that are compact, cheap and low-power, in order to enable their widespread proliferation into consumer products. Furthermore, interoperability of GNSS with non-navigation systems, especially communication systems will gain importance in providing the value added services in a variety of sectors, providing seamless quality of service for users. An important step into the market for Galileo is the timely availability of these hybrid multi-mode terminals for consumer applications. However, receiver architectures that are amenable to high-levels of integration will inevitably suffer from RF impairments hindering their easy widespread use in commercial products. This paper studies and presents analytical evaluations of the performance degradation due to the RF impairments and develops algorithms that can compensate for them in the DSP domain at the base band with complexity-reduced hardware overheads, hence, paving the way for low-power, highly integrated multi-mode GNSS receivers.

Compensation of undesired effects in MIMO wireless transceivers

This paper presents compensation of all undesired effects (Power Amplifier (PA) nonlinearity, transmitter and receiver antenna crosstalk, before-PA nonlinear crosstalk, Multiple Input Multiple Output (MIMO) channel fading and crosstalk) in MIMO Orthogonal Frequency Division Multiplex (OFDM) wireless systems. It has been demonstrated that reduced-complexity Crossover Digital Predistortion (CO-DPD) algorithm on transmitter side and Matrix Inversion algorithm on receiver side can suppress almost all undesired effects introduced by transmitter, channel and receiver in 4×4 MIMO OFDM System that can be used in modern wireless system applications. A significant complexity reduction is achieved due to the fact that Digital Signal Processing (DSP) during CO-DPD process on transmitter side is done with real instead of complex numbers.

You Should Never Look a Gift Horse in the Mouth: One-Size-Fits-All Compensation in Wrongful Conception

This article reconsiders the House of Lords decision in Rees v. Darlington Memorial Hospital NHS Trust (2003) and the decision to award a conventional award of £15,000 in all cases of failed sterilisation resulting in the birth of an unwanted child. In so doing, it briefly recites the history of the Wrongful Conception action and the unique facts of Rees. It then goes on the consider the implications of two fundamental aspects of the judgment. Firstly, it looks at the 'conventional award' itself and considers the reasoning behind the award and the effect that it has on our understanding of (particularly women's) reproductive autonomy. Secondly, it analyses the rather 'unique' judgment of Lord Scott and his decision to evaluate these cases using the possessory analogy of an unwanted foal; particular focus is given to the notion of parental 'choice' in these cases and whether mitigation (i.e. abortion or adoption) can ever be considered "reasonable".

Identification of meat spoilage by FTIR spectroscopy and neural networks

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid determination of meat spoilage, Fourier transform infrared (FTIR) spectroscopy technique, with the help of advanced learning-based methods, was attempted in this work. FTIR spectra were obtained from the surface of beef samples during aerobic storage at various temperatures, while a microbiological analysis had identified the population of Total viable counts. A fuzzy principal component algorithm has been also developed to reduce the dimensionality of the spectral data. The results confirmed the superiority of the adopted scheme compared to the partial least squares technique, currently used in food microbiology.

3D Reconstruction of Medical Images from Slices Automatically Landmarked with Growing Neural Models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

Protein deiminases: new players in the developmentally regulated loss of neural regenerative ability

Spinal cord regenerative ability is lost with development, but the mechanisms underlying this loss are still poorly understood. In chick embryos, effective regeneration does not occur after E13, when spinal cord injury induces extensive apoptotic response and tissue damage. As initial experiments showed that treatment with a calcium chelator after spinal cord injury reduced apoptosis and cavitation, we hypothesized that developmentally regulated mediators of calcium-dependent processes in secondary injury response may contribute to loss of regenerative ability. To this purpose we screened for such changes in chick spinal cords at stages of development permissive (E11) and non-permissive (E15) for regeneration. Among the developmentally regulated calcium-dependent proteins identified was PAD3, a member of the peptidylarginine deiminase (PAD) enzyme family that converts protein arginine residues to citrulline, a process known as deimination or citrullination. This post-translational modification has not been previously associated with response to injury. Following injury, PAD3 up-regulation was greater in spinal cords injured at E15 than at E11. Consistent with these differences in gene expression, deimination was more extensive at the non-regenerating stage, E15, both in the gray and white matter. As deimination paralleled the extent of apoptosis, we investigated the effect of blocking PAD activity on cell death and deiminated-histone 3, one of the PAD targets we identified by mass-spectrometry analysis of spinal cord deiminated proteins. Treatment with the PAD inhibitor, Cl-amidine, reduced the abundance of deiminated-histone 3, consistent with inhibition of PAD activity, and significantly reduced apoptosis and tissue loss following injury at E15. Altogether, our findings identify PADs and deimination as developmentally regulated modulators of secondary injury response, and suggest that PADs might be valuable therapeutic targets for spinal cord injury.

A Fuzzy-Wavelet Neural Network Model for the Detection of Meat Spoilage using an Electronic Nose

Food product safety is one of the most promising areas for the application of electronic noses. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). This paper proposes a fuzzy-wavelet neural network model which incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modeling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results indicated that the proposed modeling scheme could be considered as a valuable detection methodology in food microbiology