A single probe-fed novel V slit, stub and slot embedded circular microstrip antenna with resonances in the three bands of UMTS, worldwide interoperability for microwave access (WiMAX) and WLAN is presented. The polarisation is circular in the UMTS band and linear in the other two bands. Asymmetrical V slits in the patch boundary along with an embedded circular slot in the patch centre are employed to introduce the perturbation necessary for circular polarisation. Impedance bandwidths (BWs) of 4.2, 2 and 6.2%, respectively, in the three bands centred at 2, 3.5 and 5.6 GHz are obtained. The axial ratio BW is 2.3% in the UMTS band. Moderate gains of 4.4, 3.5 and 2.8 dBi are obtained in the three bands. There is a patch size reduction of about 48% when compared with the conventional circular patch antenna at a fixed operating frequency. The radiation pattern is directional in the WiMAX band and nearly omnidirectional in the WLAN band.

A novel composite right/left-handed substrate integrated waveguide (SIW)-based leaky wave antenna (LWA) is proposed. Square-ring-slot radiators are adopted to introduce series capacitor as well as the energy leakage, and four grounded vias within the slot ring contribute to part of the shunt inductor. Moreover, low cross-polarisation levels in the beam scanning plane are achieved due to the differential excitations of the radiators located along the centre line of the SIW working at TE10 mode. The antenna is fabricated and measured. Both simulated and measured results show that the proposed antenna is a balanced LWA operating in the frequency band 13.5–17.8 GHz. Continuous beam scanning characteristic is acquired within the scanning region −57° to +30°. In addition, low cross-polarisation levels less than −27 dB are obtained, and measured results are in good agreement with simulated ones.

A multilayer neural network, equipped with a two-memristors synapse, for speech recognition is proposed. The discussed neuromorphic neural network is a hybrid system which uses a Gaussian–Bernoulli restricted Boltzmann Machine (RBM) to transform the speech data into sparse encoded binary data. The sparse data is used to train a standard RBM, and a two-memristors synapse using AI/Pr_0.7Ca_0.3MnO₃ memristor is used as a connection between the two layers of the RBM. The simulations are performed with the real memristor's behavioural data, for potentiation and depression, to adjust learn-able parameters of the neuromorphic RBM. Instead of hard coded representation of the data, memristive synapses follow the biological way of learning for plasticity by training with examples. Experimentation with the American common use vowels and its results assert the efficacy of the proposed architecture.

Automatic diagnosis of epilepsy using electroencephalogram (EEG) signals is a hot topic in medical community as traditional diagnosis relies on tedious visual screening by highly trained clinicians from lengthy EEG recording. Hence, a new methodology to automatically detect epilepsy from EEG signals considering complex network as the principal dynamics of the epileptic EEG signals can be perfectly described by complex network is introduced. A novel edge weight method for visibility graph in the complex network for detection of epilepsy syndrome is presented. The effect of new edge weights for one key characteristic (such as, average weighted degree) of complex network is investigated. Finally, the extracted feature set is evaluated by two popular machine learning classifiers: support vector machine (SVM) with several kernel functions and linear discriminant analysis. The experimental results on Bonn University datasets show that the proposed approach is able to characterise the epilepsy from EEG signals generating up to 100% classification performance by SVM with polynomial kernel.

A low-power charge pump- and VCO-based delta-sigma ADC is presented, realising second-order noise shaping without any analogue integrator. The proposed synchronous pulse-width modulator -driven charge pump replaces an analogue integrator in delta-sigma ADC power efficiently. Together with the noise shaping provided by the VCO in the quantiser, an analogue-less 2nd-order delta-sigma ADC is obtained. The simulation results in 90 nm CMOS show that the proposed charge pump- and VCO-based delta-sigma ADC achieves 78.7 dB signal-to-noise ratio and 74.2 dB signal-to-noise and distortion ratio for a bandwidth of 2 MHz, consuming 2.95 mW, corresponding to a FoM of 0.18 pJ/conv.

A new approach for current sensor fault detection and isolation (FDI) for permanent magnet synchronous motor (PMSM) drives is presented. Contrary to the classical approaches for sensors fault diagnosis, based on residual generation through observers or parity equations, the proposed technique uses the average normalised machine-phase currents. The main advantages of this approach are that it does not need any information about the PMSM or inverter models, and it involves low tuning efforts, that make it suitable for real-time implementation with good reliability. The good performance and the robustness of the proposed FDI approach are illustrated through experimental results.

Retrieving original user data from holographic data storage systems is mainly affected by two-dimensional (2D) intersymbol interference; the minimisation of this interference not only improves the system performance, but it also increases the storage density for page-oriented storage systems. An iterative detection that is supported by the readback signal is proposed. The decoded symbols are passed through a 2D partial response target before they are combined with the output of the equaliser, leading to the generation of a refined information source that improves the channel-detection performance. The simulation results show that the proposed structure provides a gain of ∼1–2 dB; furthermore, the combinative quality of the proposed model and a page-based search scheme were analysed as well.

Logic minimisation over the basis (AND, XOR, NOT) has received much attention in recent years. Heuristic logic minimisation methods based on the notion of multiplicative complexity c _∧ (f) have reported impressive results for well-explored applications such as cryptographic S-Boxes. However, the heuristic involves randomised selections in part of its algorithm. Studying the heuristic from a consistency perspective is carried out here. Enhancements to improve different aspects of the algorithm are proposed. The benefits of the proposed enhancements are demonstrated through experimental results in comparison with the original algorithm.

Completely pipelined signal adaptive multicycle hardware design of the optimal time-frequency (TF) filter is developed and verified. The design retains all desirable characteristics of the corresponding recently proposed signal adaptive solution with the optimised time and hardware requirements, but additionally improves the execution time – for a clock cycle per each TF point performed within the estimation, resulting in the improvement of up to 50% in terms of points lying outside the instantaneous frequency of the estimated signal.

The DC-link voltage offset in three-phase four-switch (TPFS) inverter-fed permanent magnet synchronous motor (PMSM) drives deteriorates the linear modulation range severely, restricting the performance and adjustable speed range of the PMSM. An adaptive control method is proposed in this Letter to suppress the DC-link voltage offset in TPFS inverter-fed PMSM drives. By investigating the effects of four basic voltage vectors on the voltage offset, the proper compensating vectors, whose duration times are obtained by the closed-loop control, are added in each control period. Moreover, an adaptive notch filter is proposed to extract the offset component, providing excellent dynamic and steady performances even at extremely low rotor speed. Experimental results demonstrate the superiority of the proposed adaptive suppression method compared with previous methods.

Unlike traditionally studied in time domain, the creep in a piezoelectric actuator is studied in frequency domain. It is modelled as a fractional-order integrator, identified in frequency domain, and compensated for by connecting with a fractional-order differentiator in serial. It is demonstrated that identification and compensation in frequency domain are much simpler to execute than that in time domain. Experimental results validate the effectiveness of the proposed algorithm and the creep non-linearity reduces by greater than 80%.

For stereo matching, PatchMatch belief propagation (PMBP) gives an efficient way of inferencing continuous labels on the Markov random field. Nevertheless, it still requires considerable time when the resolution of input images is high. To handle high-resolution images, a two-step stereo method is proposed that efficiently exploits PMBP by depth upsampling. In the first step, PMBP is conducted on the random field whose nodes correspond to the downsampled pixels from an input image. As a result, accurate low-resolution disparity maps are efficiently obtained by taking advantage of PMBP. In the second step, the low-resolution disparity map is upsampled while considering depth boundaries and sub-pixel accuracy. Experimental results show that the proposed method provides more accurate disparity maps than the original PMBP while reducing computation time remarkably.

Person re-identification is defined as re-identifying individuals across different camera views. This is a very challenging problem since the appearance of a person can vary significantly due to cross-camera changes in viewpoint, pose and illumination. To model the transition between camera views, distance metric learning has been widely used in person re-identification and shown to be effective. However, using one specific metric often suffers from over-fitting and may not be sufficient enough to cope with the cross-camera variations of all different individuals. In this Letter, a powerful metric fusion method is proposed to combine multiple given distance metrics. Specifically, we represent given metrics as different graphs and then formulate the fusion problem as a graph-based learning framework. In this way, our framework can efficiently integrate the complementary information provided by different input metrics.

A recursive anisotropic diffusion algorithm for image denoising is proposed. Adopting the conventional anisotropic diffusion model, extending it to a recursive model leads to better noise removal with the same parameters, and equivalent or improved results with fewer iterations is showed. The reduction in the number of iterations leads to better edge preservation is also demonstrated. Visual and objective performance evaluations both show superior results compared with the classical model. Furthermore, tests on real medical images show successful noise removal with good edge preservation.

Channel estimation is a big challenge in multiuser massive multiple-input multiple-output systems. A novel multiuser differential transmission scheme for uplink transmission with a large antenna array at the base station (BS) is proposed. In the proposed scheme, a block-by-block differential encoder is employed at each user, while simple symbol-wise differential decoder is used at the BS to recover the information symbols without any knowledge of the channel state information (CSI). The performance of the proposed scheme when the number of BS antennas grows large is analysed. Both analytical and numerical results show that the proposed differential transmission scheme is able to achieve almost the same bit-to-error rate performance as the coherent maximum ratio combining receiver with perfect CSI in the high signal-to-noise ratio region.

Quantised kernel least mean square algorithm with fixed budget (QKLMS-FB) is an effective method for constraining the final network size of QKLMS at the cost of less accuracy loss. However, the significances of all centres in the dictionary are required to be calculated at each iteration, which will lead to linear increasing in the computational complexity of QKLMS-FB with the centre number. To reduce the computational cost and retain a better accuracy simultaneously, only the coefficient vector and influence factor are incorporated to measure the significance of each centre, thereby generating a novel simplified QKLMS-FB (SQKLMS-FB). In addition, the gradient descent method is applied in the SQKLMS-FB to update the coefficient of the closest centre for accuracy improvement. Simulations both in stationary and non-stationary cases validate the proposed SQKLMS-FB.

A novel 2D finite difference time domain (FDTD) subgridding method is proposed, only subject to the Courant limit of the coarse grid. By making μ or ε inside the subgrid dispersive, unconditional stability is induced at the cost of a sparse, implicit set of update equations. By only adding dispersion along preferential directions, it is possible to dramatically reduce the rank of the matrix equation that needs to be solved.

In this Letter, two constructions of new binary sequences with optimal autocorrelation magnitude of length 4N derived from binary sequences with optimal autocorrelation of length N = 2 (mod 4) and almost-perfect binary sequences of length 2N using N × 2 interleaved structure is presented. The first construction is to use binary Sidelnikov sequences of length N = pⁿ −1 whereas the second one is to use binary Ding–Helleseth–Martinsen sequences of length N = 2p. The obtained sequences have large linear complexity and can be used in communication and cryptography.

A sketch-guided filtering scheme for assisting superspreader detection in the measurement of high-speed network traffic is proposed. The scheme comprises of an array of linear-counting sketches that rapidly eliminates flows with potentially low fan-out during a measurement interval. Based on the results of simulations obtained using real-world network traces, the filter can eliminate up to 90% of the flows of non-superspreader sources and improve the accuracy of superspreader identification. Furthermore, the proposed scheme has a smaller fan-out estimation error and consumes less memory than previously developed approaches. The hardware implementation can process network traffic at a throughput of 27 Gbit/s.

A sparse set-membership normalised least mean square (SM-NLMS) algorithm with a correntropy penalty is proposed and its performance is investigated for estimating a sparse echo channel. The proposed sparse SM-NLMS algorithm is derived by minimising an unconstraint cost function that utilises the correntropy on the weight vector as well as the sum of a symmetric and positive definite matrix constrained Euclidean norm of the differences between the instantaneous error and the upper bound of the SM filtering. Simulation results over a sparse echo channel show that the proposed algorithm is superior to the existing algorithms with respect to the steady-state misalignment.

Compact quint-band bandpass filter (QB-BPF) based on a novel penta-mode resonator (PMR) is presented. The first five resonant modes of the proposed PMR can be independently controlled by shorted high-impedance section of quarter-wave stepped impedance resonators, and four loaded open stubs resulting in the independency of centre frequencies and quality factors of five passbands. Meanwhile, due to the multipath propagation induced from cross-coupling, 11 transmission zeros are realised around five passbands, resulting in high passband selectivity. As an example, a QB-BPF operating at 0.63/1.2/1.8/2.45/3.5 GHz is designed and fabricated. The fabricated QB-BPF also has a compact size of 0.18λ _g × 0.12λ _g.

A novel air-filled E-plane rectangular waveguide (RWG) to substrate integrated waveguide (SIW) transition, which is suitable for Ka-band large-scale antenna arrays, is presented. The power is coupled between the RWG and SIW through two slots: one etched on the SIW ground plane and the other cut through metallic RWG narrow side wall (E-plane). A back-to-back transition is designed, fabricated, assembled, and tested. Measured results show a good agreement with the simulated ones. An SIW attenuation loss ≤0.33 dB/1 cm and a transition return loss better than 10 dB have been experimentally obtained over the band 28.30–30.8 GHz.

A novel filtering push–pull power amplifier (PPPA), based on unbalanced-to-balanced impedance transformers, is presented for the first time. This novel impedance transformer can not only simplify the PPPA topology and miniaturise the overall circuit size, but also provide the bandpass filtering response and improve the second harmonic suppression performance. The proposed impedance transformers, which are constructed by two different C-type line resonators, can provide good impedance matching performance under the odd-mode excitation, while achieve high common mode suppression under the even-mode excitation. Finally, a PPPA is designed and fabricated with the centre frequency of 2.45 GHz and bandwidth of 200 MHz for WLAN application. Moreover, detailed explanation and measured results are demonstrated for verification.

A novel wideband bandstop filter (BSF) with a minimum attenuation better than 28.5 dB and three transmission zeros within the stopband is proposed. The designed filter is composed of a top microstrip transmission line and a bottom coplanar waveguide open-circuited resonator loaded by a periodical L-shaped defected ground structure resonant unit cell. The top and bottom dual-metal-plane conductors are connected by the periodically metallic via-hole within the designed substrate. With the appropriate height of substrate and separation between the adjacent metallic via-holes, an excellent parallel-plate-metal synthesised transmission line with an improved coupling between the top and bottom resonators can be achieved by this via-hole-loaded technology. Finally, a microstrip BSF centred at 5.44 GHz with a measured 20 dB rejection bandwidth of more than 35.5% are designed, fabricated, and measured for this topology of validation.

A novel transmission system that adaptively compensates for intra- and inter-channel nonlinear distortions while alleviating the computation load is described. It does so by using an optical dispersion compensation at optical nodes and a Volterra-based multi-channel nonlinear equalisation. Simulation results show that 3.8 dB Q-factor improvements are obtained against conventional systems that do not compensate for nonlinear distortions.

The ultrasonic welding of polymer optical fibres (POFs) onto carbon-fibre-reinforced polymers for advanced fibre-optic sensing is demonstrated. The relationships among the welding time, preload, optical loss, and adhesive force are fully evaluated. A high-speed camera to monitor changes in the cross section of the POF during the ultrasonic welding is also used.

Silicon carbide-based quasi-separated-absorption-multiplication ultraviolet avalanche photodiode (APD) with a small-area multiplication region and a large-area absorption region, which comprises of a p⁺nn⁻ junction encircled by a p⁺n⁻ junction, is proposed, and its optoelectronic performance is modelled. The modelling results show a 4H-SiC APD with high performance can be achieved. Moreover, when operated at a low reverse bias (e.g. 5.0 V), the photodiode has almost the same optoelectronic characteristics as the 4H-SiC p-i-n photodiode. It is noted that the device has benefited advantages of both conventional separate absorption and multiplication APD and p-i-n photodiode in the wavelength range of ultraviolet detection, which enable the dual operation models of the device.

A new flipping magnet type electromagnetic energy harvester (EEH) suitable for scavenging energy from low frequency vibrations is presented in this Letter. The proposed EEH has a spherical permanent magnet (SPM), which is free to move inside a spherical bobbin that carries coils. Two cylindrical permanent magnets are employed to flip the SPM fast, even if the frequency of vibration source is low. This induces sufficient voltage in the coil to convert to dc and use. No such scheme has been reported so far and the existing EEHs give very low induced voltage for low frequency vibrations <5 Hz. Two versions of the new EEH prototypes, were built and tested. The peak-to-peak open circuit voltage of version-1 was 3.5 V and the power density was 445 µW/cm³ for a matched load of 52.5 Ω at 3.5 Hz vibration. The power density of the version-2 harvester was 538.6 µW/cm³. One of the applications of the proposed EEH is to harvest energy from railway tracks, for powering trackside monitoring sensors. The prototype developed generated up to 2.44 mW for an emulated railway track vibration in the range of 4 Hz, which is a considerable improvement compared with the existing EEHs.

Commercially available supercapacitors currently require designers to experimentally characterise devices before integration for their specific applications. In this work a simple fractional-order equivalent model for a supercapacitor is used to derive the design equation to estimate the discharge time due to a constant current. This model is shown to capture the transient discharging behaviour in the voltage range of interest (5–3 V) typical of many embedded systems. Experimental results using Kemet FT0H105ZF supercapacitors (1 F rating) as a secondary power supply for an Arduino Uno system are presented to highlight the application of this model and equations to a ubiquitous embedded system.

Range and azimuth spatial-variant phase errors are usually presented in high-resolution inverse synthetic aperture radar imagery as the manoeuvring motion of the observed targets. It could not be effectively compensated by the traditional autofocus algorithms. A new method is proposed for 2D spatial-variant phase errors compensation based on contrast maximisation. First, a novel phase error parametrical signal model is established. Then, image contrast is introduced as a cost function, and an iterative, modified gradient-based method is used to solve a maximal contrast optimisation problem. The proposed method has a good convergence within a few iterations. The public data provided by the Naval Research Laboratory is utilised to confirm the effectiveness and superiorities of the proposed method.

A method of current velocity estimation using airborne sea data is proposed. The sea data are collected by circular synthetic aperture radar. The range Doppler image can be acquired after range and azimuth compression for each beam scan angle. The corresponding average Doppler spectrum can be obtained and fitted to Gaussian shape well. Hence, the Doppler centre shift can be represented by the mean of Doppler spectrum. It is observed that the Doppler centre varies with the beam scan angle and the variation is approximately a sinusoid-shape function. The velocity and direction of current in a local area are fixed so the radial velocity caused by the current is a harmonic function of the scan angle. Therefore, the current velocity can be obtained by the amplitude of the harmonic. Actually, the radial velocity does not only include the current, but also includes the surface wave motion. However, the method presented can obtain the real current velocity directly, avoiding adopting the radial velocity of the scatterer, so the estimation of the current velocity is accurate.

A simple software correction algorithm based on the empirical mode decomposition (EMD) algorithm to correct the nonlinearity of a VCO is proposed. The proposed algorithm divides a dechirp signal into mono-component signals using EMD so that the nonlinearity is extracted from the decomposed components in the form of phase distortion. The phase distortion due to nonlinearity is compensated by using the resampling method. As a result, the proposed algorithm corrects the phase distortion without assistance from any additional hardware, thus maintaining simplicity and cost effectiveness. The proposed algorithm is verified by a simulation and an experiment, and it yields well corrected range profiles.

Two improved estimators for estimating the shape parameter of multilook Pareto distribution are proposed. The proposed estimators are aimed at widening the valid estimation range of the shape parameter by using the assemble averages <z ^r > and <z ^r log z>. Moreover, the estimators are closed-form if r takes the negative integers. Compared with the existing estimators which are either non-closed-form or invalid for small shape parameters, the proposed estimators can estimate the shape parameter in the whole range from zero to infinity with closed forms. Simulation results demonstrate the better estimation performance of the proposed estimators.

The mechanism of hot-carrier-induced drain breakdown voltage walkout in an n-type lateral diffused MOS transistor is investigated. On the basis of the data of charge pumping measurement, hot-carrier-induced interface states created at the accumulation region is proposed to be responsible for the breakdown walkout. Further technology computer-aided-design simulations also support the before-mentioned mechanism.

An extremely accurate yet simple form of the charge-sheet model (CSM) is developed using the third-order Hermite interpolation polynomial to model the inversion charge in the channel. This new formulation of the drain current retains the same simplicity of the most advanced surface potential compact MOSFET models based on the symmetric linearisation method (SLM). However, unlike the SLM, it is developed without requiring the crude linearisation of the inversion charge, hence the asymmetry and the non-linearity in the channel are accurately accounted for. Nevertheless, the expression of the drain current can be worked out to be analytically equivalent to SLM. Its mathematic formulation is even easier with respect to SLM since it does not require the evaluation of the inversion charge at the surface potential midpoint, but at source and drain only, as the conventional CSM.

The impact of the AC signal oscillator level on the effective mobility measurement by split C–V technique in MOSFETs is investigated. It is found that, due to strong nonlinearity below threshold, the gate-to-channel capacitance and, by turn, the channel inversion charge increases linearly with the oscillator level. As a consequence, the extracted effective mobility decreases linearly with the oscillator level, resulting in a huge underestimation of the effective mobility in weak inversion. A physical model explaining these behaviours is developed, which enables to obtain a quantitative description of both inversion charge and effective mobility variations with the oscillator level and the gate voltage.

Sequential order one negative exponential (SOONE) function is used to measure the sparsity of a two-dimensional (2D) signal. A 2D gradient projection (GP) method is developed to solve the SOONE function and thus the 2D-GP-SOONE algorithm is proposed. The algorithm can solve the sparse recovery of 2D signals directly. Theoretical analysis and simulation results show that the 2D-GP-SOONE algorithm has a better performance compared with the 2D smoothed L0 algorithm. Simulation results also show that the proposed algorithm has a better performance and requires less computation time than 2D iterative adaptive approach.

A driver state estimation algorithm that uses multimodal vehicular and physiological sensor data is proposed. Deep learning is applied to the fused multimodal data rather than each modality being treated as a different feature. A convolutional neural network model is developed and the driver state estimation algorithm is implemented using Google TensorFlow. The results show that deep learning is a very promising approach for driver state estimation compared with previously studied algorithms, such as dynamic Bayesian networks.

The support recovery performance of orthogonal matching pursuit (OMP) for the l _∞ bounded noise is presented. It is shown that OMP can exactly recover the support of arbitrary K-sparse signal x from noisy measurements y = Φ x + e in K iterations, provided that the matrix Φ and the minimum magnitude of all the non-zero elements of x satisfy certain requirements. The proposed result is an improvement over the existing ones.

A two-channel single-stage switching amplifier (SSA) based on high-frequency link inverter is proposed. The audio input signals are modulated by phase shift between primary-side switches and secondary-side switches, thus independent amplifications of two channels can be obtained. Benefiting from multiplexing of primary-side power switches for two channels, only a half bridge inverter is utilised at primary side. Clamp circuits at the secondary side of transformer eliminate spike voltages across the secondary-side switches during the current commutation of the cycloconverters. Zero voltage switching of primary-side switches and clamp switches are achieved by utilising magnetising inductor current. A 320 V/250W prototype is presented to verify the analysis results of the proposed two-channel SSA.

Near-field acoustical holography methods have bad resolution at medium-to-high frequencies. This is especially a problem for three-dimensional source identification, when the microphone array is not arranged around the source. To overcome this issue, an improved equivalent source method (IESM) with two mutually perpendicular sub-arrays is used. Similar to the equivalent source method, the equivalent source strengths of IESM can be evaluated by the steepest descend method on both sets of microphones. Using two perpendicular planar arrays surrounding the source, the spatial resolution of IESM can be improved in both directions. By introducing the steepest descend and threshold filtering method, IESM based on two mutually perpendicular planar arrays can suppress the ghost sources associated with the real sources. Hence, it can identify the main sources much more accurately at medium-to-high frequencies. The proposed method also is used on both synthetic and experimental data. The results also showed that IESM give source maps that are more interpretable than conventional near-field acoustical holography methods.

A new interference-aware frequency hopping (IAFH) scheme for Bluetooth to mitigate the interference from Wi-Fi networks is proposed. The conventional adaptive frequency hopping (AFH) scheme classifies channels into ‘good’ or ‘bad’ according to the predefined threshold and uses good channels with a uniform hop probability. Unlike the conventional AFH scheme, the proposed IAFH dynamically classifies channels into ‘good’ or ‘bad’ according to the observed interference levels and uses good channels with non-uniform hop probabilities. The simulation results demonstrate that the proposed IAFH scheme significantly outperforms the conventional AFH scheme.