In order to address a wide variety of future requirements, Generalized Frequency Division Multiplexing (GFDM), a non-orthogonal multicarrier scheme, is considered as one of the most promising techniques available today. To improve the orthogonality of the conventional GFDM system, a multi taper implementation of GFDM (MGFDM) using discrete prolate spheroidal sequences (DPSSs) or multi-tapers, which have lower out of band (OOB) radiation, can be exploited for pulse shaping the individual subcarriers. For reliable data communications, we propose in this article a combination of a convolution code with an MGFDM system to improve the Bit Error Rate (BER) performance. The standard convolution code (7, [171,133]), commonly used in most wireless systems is employed. Simulated BER performance of coded MGFDM (CMGFDM) along with conventional GFDM is investigated. The results show an improvement in the performance of CMGFDM when compared to MGFDM and GFDM systems. Also, an analysis on different receivers namely, Zero Forcing (ZF) and Matched Filter (MF) is studied and the Peak-to-average power ratio (PAPR) of the proposed CMGFDM system is evaluated.

Recent activities in the cellular network world clearly show the need to design new physical layer waveforms in order to meet future wireless requirements. Generalized Frequency Division Multiplexing (GFDM) is one of the leading candidates for 5G and one of its key features is the usage of circular pulse shaping of subcarriers to remove prototype filter transients. Due to the nonorthogonal nature of the conventional GFDM system, inherent interference will affect adversely channel estimation. With Discrete Prolate Spheroidal Sequences (DPSSs) or multitapers as prototype filters an improved orthogonal GFDM system can be developed. In this work, we investigate channel estimation methods for multitaper GFDM(MGFDM) systems with and without Discrete Fourier Transform(DFT). The simulation results are presented using Least Squares (LS) and Minimum Mean Square Error(MMSE) channel estimation (CE) methods. DFT based CE methods provide better estimates of the channel but with an additional computational cost.

Generalized Frequency Division Multiplexing (GFDM) has been proposed recently as a candidate for the next generation wireless communications systems (5G) due to its attractive properties that seem to cover the envisioned applications. In order to make GFDM more robust to multipath fading effects the techniques of space-time block codes (STBC) can be added to its implementation. In this article, we consider the performance of orthogonal space-time block coded (OSTBC) GFDM systems over Rayleigh fading channel. In addition, to further enhance performance, Discrete Prolate Spheroidal Sequences (DPSSs or multi-tapers) can be exploited to turn conventional GFDM to an improved orthogonal system. In this work we investigated a precoded OSTBC Multitaper GFDM system along with conventional GFDM. The symbol error rate (SER) performance for precoded OSTBC-(M)GFDM systems over a Rayleigh fading channel is examined and a good match between simulation results and analytical expressions is seen to exist.

Generalised frequency division multiplexing (GFDM) is one of the promising contenders for fifth generation (5G) wireless communications. It is of great interest as it shows a number of advantages over cyclic prefix orthogonal FDM (CP-OFDM). However, the non-orthogonality scheme of GFDM introduces intersymbol and intercarrier interference (ISI/ICI). In order to mitigate these effects we explore the near orthogonality concept of offset quadrature qmplitude modulation (OQAM). A novel preliminary analysis of GFDM/OQAM is investigated in the presence of both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels and it is seen that the symbol error rate (SER) performance, computed through simulations and analytical expressions, is improved.

Future wireless communication systems demand faster communications, massive access, high mobility, relaxed synchronization and also a very low latency. Generalized Frequency Division Multiplexing (GFDM) a candidate for 5G, is a non-orthogonal based multi-carrier technique with a flexible frame structure of M time slots per K subcarriers and a free choice of pulse shaping filter. However, due to the inherent non-orthogonal nature of the subcarriers there is a performance degradation. This paper discusses the preliminary performance evaluation of a GFDM based digital communication system with prolate spheroidal (multi-taper) windows versus conventional GFDM. The introduction of prolate spheroidal windows as pulse shaping filters can compensate for orthogonality loss, eventually turning conventional GFDM into an improved, orthogonal system. GFDM using these windows outperforms conventional GFDM in terms of symbol error rate (SER) performance in fading multipath channels. Furthermore, the analytical equations of the above performance in conventional GFDM are extended to cover the multi-taper case and the analytical results are compared with simulations.

Purpose– The purpose of this paper is to study the performance of generalized frequency division multiplexing (GFDM) in some frequency selective fading channels. The exact symbol error rate (SER) expressions in Hoyt (Nakagami-q) and Weibull-vfading channels are derived. A GFDM transceiver simulation test bed is provided to validate the obtained analytical expressions.Design/methodology/approach– Modern cellular system demands higher data rates, very low-latency transmissions and sensors with ultra low-power consumption. Current cellular systems of the fourth generation (4G) are not able to meet these emerging demands of future mobile communication systems. To address this requirement, GFDM, a novel multi-carrier modulation technique is proposed to satisfy the future needs of fifth generation technology. GFDM is a block-based transmission method where pulse shaping is applied circularly to individual subcarriers. Unlike traditional orthogonal frequency division multiplexing, GFDM transmits multiple symbols per subcarrier. The authors have used the probability density function approach in solving the final analytical expressions.Findings– Detailed analysis of GFDM performance under Hoyt-q, Weibull-vand Log-Normal Shadowing fading channels. Exact analytical formulae were derived which support the simulations carried out by authors and other authors. The exact dependence of SER on fading parameters and roll-off factorαin the raised cosine pulse shape filter was determined.Practical implications– Development and fabrication of high-performance GFDM systems under fading channel conditions.Originality/value– Theoretical support to simulated system performance.

Generalized Frequency Division Multiplexing (GFDM) is a multi-carrier modulation scheme proposed for the next generation (5G) wireless systems. Trading orthogonality for Inter Symbol Interference (ISI) and Inter Carrier Interference (ICI) control it provides a structure with better usability for a variety of future wireless requirements. In this paper the exact Symbol Error Rate (SER) expressions of GFDM in Nakagami-m and Rician fading channels are analytically derived. A GFDM tranceiver is also simulated and the results are compared with the analytic expressions.

Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost.

This paper discusses the design and implementation of a prototype system for on/off switching of electrical appliances through an AVR ATmega16 microcontroller based on external temperature sensor stimuli. The development of firmware code in C that implements this simple switching and the potential for more sophisticated automation/control scenarios will be described. The graphical monitoring of the sensor data through a serial port connection to a PC will also be described. Starting from a well defined list of requirements all the necessary steps involved in the final implementation of the prototype will be described from the point of view of an Electrical Engineering student doing his final year project. Parts of the work required skill sets and knowledge not covered in the regular student coursework. Useful results on how the current Electrical Engineering curriculum of TEI Patras can be modified for the benefit of future students will also be outlined.

This paper discusses the performance evaluation of two sets of commercially available PLC modems. The two sets are tested in various locations within the power distribution network of TEI Patras, in offices and labs equipped with heavy machinery in active condition. The results under normal and severe conditions show the average throughput achieved in low and high intensity operating conditions as well as corresponding performance limitations. The process involved provides valuable information on the usage of such devices in power distribution networks of residential, office and light industry environments.

Facial expression and hand gesture analysis plays a fundamental part in emotionally rich man-machine interaction (MMI) systems, since it employs universally accepted non-verbal cues to estimate the users’ emotional state. In this paper, we present a systematic approach to extracting expression related features from image sequences and inferring an emotional state via an intelligent rule-based system. MMI systems can benefit from these concepts by adapting their functionality and presentation with respect to user reactions or by employing agent-based interfaces to deal with specific emotional states, such as frustration or anger.

In this paper, we address the problem of 3d motion and structure estimation of 3d objects appearing in 2d images; namely, the estimation of the parameters of 3d motion, such as rotation and translation in 3d space, and the third dimension of certain objects that can be seen in a time sequence of 2d images. The study of the problem will be restricted to the case of non-rigid objects. The main problem with non-rigid motion is that it is not structured in a way that would allow its estimation with a few parameters, as in the case of rigid motion. That is why the main effort in most of the approaches is in representing deformable objects with suitable models that require only a small number of parameters for their description. In this work we perform a survey of algorithms proposed for the 3d motion and structure estimation of non-rigid objects, using the Finite Element Method. A classification of established algorithms is presented, with respect to the actual technique utilized and the applications for which they are most suitable.

Recently, neural networks have been proposed for radar clutter modeling because of the inherent nonlinearity of clutter signals. This paper performs an analysis of the practicality of using a radial basis function (RBF) neural network to model sea clutter and to detect small target embedded in sea clutter. An experiment using an instrumental quality radar was carried out on the eastcoast of Canada to create a rich sea clutter and small surface target database. This database contains both staring and scanning data under various environmental conditions. Using data-sets with different characteristics, we investigate the effects of quantization error, measurement noise, generalization of the neural net over ranges and sampling rate on the RBF clutter model. Despite these physical limitations, the RBF model was shown to approach an optimal predictive performance. The RBF predictor was also applied to detect various small targets in this database based on the constant false alarm rate (CFAR) principle. This RBF-CFAR detector was demonstrated to be able to detect small floating targets even in rough sea conditions.

Over the past few years, virtual studios applications have significantly attracted the attention of the entertainment industry. Optical tracking systems for virtual sets production have become particularly popular tending to substitute electro-mechanical ones. In this work, an existing optical tracking system is revisited, in order to tackle with inherent degenerate cases; namely, reduction of the perspective projection model to the orthographic one and blurring of the blue screen. In this context, we propose a simple algorithm for 3D motion estimation under orthography using 3D-to-2D line correspondences. In addition, the watershed algorithm is employed for successful feature extraction in the presence of defocus or motion blur

Conventional detection methods used in current marine radar systems do not perform efficiently in detecting small targets embedded in a clutter environment. Based on a recent observation that sea clutter, radar echoes from a sea surface, is chaotic rather than random, we propose using a spatial temporal predictor to reconstruct the chaotic dynamic of sea clutter because electromagnetic wave scattering is a spatial temporal phenomenon which is physically modeled by partial differential equations. The spatial temporal predictor used here is called radial basis function coupled map lattice (RBF-CML) which uses a linear combiner to fuse either measurements in different spatial domains for an RBF prediction or predictions from several RBF nets operated on different spatial regions. Using real-life radar data, it is shown that the RBF-CML is an effective method to reconstruct the sea clutter dynamic. The RBF-CML predictor is then applied to detect small targets in sea clutter using the constant false alarm rate (CFAR) principle. The spatial temporal approach is shown, both theoretically and experimentally, to be superior to a conventional CFAR detector.

The generalized compound probability density function (GC-pdf) is presented for modeling high resolution radar clutter. In particular, the model is used to describe deviation of the speckle component from the Rayleigh to Weibull or other pdfs with longer tails. The GC-pdf is formed using the generalized gamma (G/spl Gamma/) pdf to describe both the speckle and the modulation component of the radar clutter. The proposed model is analyzed and thermal noise is incorporated into it. The validation of the GC-pdf with real data is carried out employing the statistical moments as well as goodness-of-fit tests. A large variety of experimental data is used for this purpose. The GC-pdf outperforms the K-pdf in modeling high resolution radar clutter and reveals its structural characteristics.

In this paper we present a method to obtain a maximum likelihood estimation of the parameters of the Generalized Gamma and K probability density functions. Explicit closed form expressions are derived between the model parameters and the experimental data. Due to their nonlinear nature global optimization techniques are used for solving the derive expressions with respect to clutter model parameters. Experimental results show in all attempted cases that the resulting expressions are convex functions of the parameters. In addition to the maximum likelihood solution we present two other solutions. One is based on moment and the other on histogram matching.

In this paper we present a method to obtain a maximum likelihood estimation of the parameters of the Generalized Gamma and K probability density functions. Explicit closed form expressions are derived between the model parameters and the experimental data. Due to their nonlinear nature global optimization techniques are proposed for solving the derived expresings with respect to clutter model parameters. Experimental results show in all attempted cases that the resulting expressions are convex functions of the parameters. In addition to the maximum likelihood solution we present two other solutions. One is based on moment and the other on histogram matching. The Cramer-Rao Lower Bound is also derived and used for performance comparisons.