Visual scene recognition with biologically relevant generative models

This research focuses on developing visual object categorization methodologies that are based on machine learning techniques and biologically inspired generative models of visual scene recognition. Modelling the statistical variability in visual patterns, in the space of features extracted from them by an appropriate low level signal processing technique, is an important matter of investigation for both humans and machines. To study this problem, we have examined in detail two recent probabilistic models of vision: a simple multivariate Gaussian model as suggested by (Karklin & Lewicki, 2009) and a restricted Boltzmann machine (RBM) proposed by (Hinton, 2002). Both the models have been widely used for visual object classification and scene analysis tasks before. This research highlights that these models on their own are not plausible enough to perform the classification task, and suggests Fisher kernel as a means of inducing discrimination into these models for classification power. Our empirical results on standard benchmark data sets reveal that the classification performance of these generative models could be significantly boosted near to the state of the art performance, by drawing a Fisher kernel from compact generative models that computes the data labels in a fraction of total computation time. We compare the proposed technique with other distance based and kernel based classifiers to show how computationally efficient the Fisher kernels are. To the best of our knowledge, Fisher kernel has not been drawn from the RBM before, so the work presented in the thesis is novel in terms of its idea and application to vision problem

Orthogonal Time Frequency Space (OTFS) Modulation for Wireless Communications

The orthogonal time frequency space (OTFS) modulation is a recently proposed multi-carrier transmission scheme, which innovatively multiplexes the information symbols in the delay-Doppler (DD) domain instead of the conventional time-frequency (TF) domain. The DD domain symbol multiplexing gives rise to a direct interaction between the DD domain information symbols and DD domain channel responses, which are usually quasi-static, compact, separable, and potentially sparse. Therefore, OTFS modulation enjoys appealing advantages over the conventional orthogonal frequency-division multiplexing (OFDM) modulation for wireless communications. In this thesis, we investigate the related subjects of OTFS modulation for wireless communications, specifically focusing on its signal detection, performance analysis, and applications. In specific, we first offer a literature review on the OTFS modulation in Chapter~1. Furthermore, a summary of wireless channels is given in Chapter 2. In particular, we discuss the characteristics of wireless channels in different domains and compare their properties. In Chapter 3, we present a detailed derivation of the OTFS concept based on the theory of Zak transform (ZT) and discrete Zak transform (DZT). We unveil the connections between OTFS modulation and DZT, where the DD domain interpretations of key components for modulation, such as pulse shaping, and matched-filtering, are highlighted. The main research contributions of this thesis appear in Chapter 4 to Chapter 7. In Chapter 4, we introduce the hybrid maximum a posteriori (MAP) and parallel interference cancellation (PIC) detection. This detection approach exploits the power discrepancy among different resolvable paths and can obtain near-optimal error performance with a reduced complexity. In Chapter 5, we propose the cross domain iterative detection for OTFS modulation by leveraging the unitary transformations among different domains. After presenting the key concepts of the cross domain iterative detection, we study its performance via state evolution. We show that the cross domain iterative detection can approach the optimal error performance theoretically. Our numerical results agree with our theoretical analysis and demonstrate a significant performance improvement compared to conventional OTFS detection methods. In Chapter 6, we investigate the error performance for coded OTFS systems based on the pairwise-error probability (PEP) analysis. We show that there exists a fundamental trade-off between the coding gain and the diversity gain for coded OTFS systems. According to this trade-off, we further provide some rule-of-thumb guidelines for code design in OTFS systems. In Chapter 7, we study the potential of OTFS modulation in integrated sensing and communication (ISAC) transmissions. We propose the concept of spatial-spreading to facilitate the ISAC design, which is able to discretize the angular domain, resulting in simple and insightful input-output relationships for both radar sensing and communication. Based on spatial-spreading, we verify the effectiveness of OTFS modulation in ISAC transmissions and demonstrate the performance improvements in comparison to the OFDM counterpart. A summary of this thesis is presented in Chapter 8, where we also discuss some potential research directions on OTFS modulation. The concept of OTFS modulation and the elegant theory of DD domain communication may have opened a new gate for the development of wireless communications, which is worthy to be further explored

Signal optimization for Galileo evolution

Global Navigation Satellite System (GNSS) are present in our daily lives. Moreover, new users areemerging with further operation needs involving a constant evolution of the current navigationsystems. In the current framework of Galileo (GNSS European system) and especially within theGalileo E1 Open Service (OS), adding a new acquisition aiding signal could contribute to providehigher resilience at the acquisition phase, as well as to reduce the time to first fix (TTFF).Designing a new GNSS signal is always a trade-off between several performance figures of merit.The most relevant are the position accuracy, the sensitivity and the TTFF. However, if oneconsiders that the signal acquisition phase is the goal to design, the sensitivity and the TTFF havea higher relevance. Considering that, in this thesis it is presented the joint design of a GNSS signaland the message structure to propose a new Galileo 2nd generation signal, which provides ahigher sensitivity in the receiver and reduce the TTFF. Several aspects have been addressed inorder to design a new signal component. Firstly, the spreading modulation definition must considerthe radio frequency compatibility in order to cause acceptable level of interference inside the band.Moreover, the spreading modulation should provide good correlation properties and goodresistance against the multipath in order to enhance the receiver sensitivity and to reduce theTTFF. Secondly, the choice of the new PRN code is also crucial in order to ease the acquisitionphase. A simple model criterion based on a weighted cost function is used to evaluate the PRNcodes performance. This weighted cost function takes into account different figures of merit suchas the autocorrelation, the cross-correlation and the power spectral density. Thirdly, the design ofthe channel coding scheme is always connected with the structure of the message. A joint designbetween the message structure and the channel coding scheme can provide both, reducing theTTFF and an enhancement of the resilience of the decoded data. In this this, a new method to codesign the message structure and the channel coding scheme for the new G2G signal isproposed. This method provides the guideline to design a message structure whose the channelcoding scheme is characterized by the full diversity, the Maximum Distance Separable (MDS) andthe rate compatible properties. The channel coding is essential in order to enhance the datademodulation performance, especially in harsh environments. However, this process can be verysensitive to the correct computation of the decoder input. Significant improvements were obtainedby considering soft inputs channel decoders, through the Log Likelihood Ratio LLRs computation.However, the complete knowledge of the channel state information (CSI) was usually considered,which it is infrequently in real scenarios. In this thesis, we provide new methods to compute LLRlinear approximations, under the jamming and the block fading channels, considering somestatistical CSI. Finally, to transmit a new signal in the same carrier frequency and using the sameHigh Power Amplifier (HPA) generates constraints in the multiplexing design, since a constant orquasi constant envelope is needed in order to decrease the non-linear distortions. Moreover, themultiplexing design should provide high power efficiency to not waste the transmitted satellitepower. Considering the precedent, in this thesis, we evaluate different multiplexing methods,which search to integrate a new binary signal in the Galileo E1 band while enhancing thetransmitted power efficiency. Besides that, even if the work is focused on the Galileo E1, many ofthe concepts and methodologies can be easily extended to any GNSS signa