Discrete Fourier Transform (DFT) based beam-formers provide N beams with a uniform linear array having N antennas. Despite low-complexity, DFT beamformers cannot generate deep nulls at arbitrary directions of arrivals (DOAs) in the beam pattern to attenuate interferences. On the other hand, data-dependent adaptive beamformers can achieve deep nulls at arbitrary DOAs, however, at higher complexity due to an inversion of a matrix in deriving optimum weights. In this paper, we propose a combined approximate DFT (ADFT) and adaptive beamformer for a uniform linear array consisting of P subarrays, each consisting of M antennas. Here, we first employ P ADFT beamformers to process signals received by subarrays, and the P outputs of these subarrays are then processed by an adaptive beamformer. Simulation results confirm that the proposed beamformer provides the benefits of both DFT and adaptive beamformers. Furthermore, we present preliminary results of an experimental antenna array operating at 5.75 GHz, where a Howells-Applebaum beamformer is employed as the adaptive beamformer.

The combined use of algorithms for approximate discrete cosine transform (DCT) with approximate computing is examined toward area-efficient field programmable gate array (FPGA) hardware architectures. The performance of previously reported, multiplierless approximate DCT transforms are explored in the presence of non-exact hardware adders which provide better utilisation of FPGA resources in terms of look-up-tables (LUTs). In the context of 2D image compression, provided examples are demonstrating a 20% LUT reduction in FPGA utilization compared to accurate adders, with a corresponding image quality degradation of 0.6 dB in terms of PSNR. The potential benefit of such area-efficient FPGA hardware designs is explored on 3D (video compression), 4D (static light field compression), and 5D (light field video compression) cases where significant FPGA resource savings are obtained at the cost of marginal degradation of output quality.

We propose a minimax design method for multi-dimensional (M-D) interpolated finite-support impulse response (IFIR) filters. As a result of the cascade structure of an MD IFIR filter, the optimization problem of the minimax design is nonconvex. In order to solve this nonconvex optimization problem, we employ a convex-concave procedure, where each iteration solves a convex constrained optimization problem. We present experimental results to confirm the effectiveness and the superior performance of the proposed method compared to previously proposed minimax designs of M-D IFIR filters. Furthermore, we present an implementation of M-D IFIR filter on the Xilinx Kintex UltraScale KCU105 field-programmable gate array, where a quantization error of −60.59 dB is achieved with the coefficient word length of 24 bits.

Chromatic derivatives (CDs) and associated chromatic approximations (CAs) provide a numerically robust and powerful framework for digital processing of continuous-time/space signals, using not only the discrete signal amplitudes, but also higher order derivatives. Acquisition of CDs has so far been limited to software implementations. This paper presents field-programmable gate array (FPGA)-based digital hardware architectures suitable for the real-time acquisition of CDs, thus enabling CDs to be used for practical signal processing algorithm development in embedded systems. With 24 bits of fixed-point precision, the proposed hardware architectures provide approximate 116 dB accuracy in the frequency responses of FIR filters capturing the CDs, and 76.85 dB and 75.09 dB accuracy in signal reconstruction with synthetic and real audio signals using CDs up to order 28 degrees. The designs have been verified on an AMD Kintex UltraScale KCU105 FGPA device using bit-true cycle-accurate hardware co-simulation.

Two-dimensional (2-D) infinite-extent impulse response (IIR) filter design is a challenging problem due to the difficulty in verifying stability. optimization methods proposed so far predominantly consider the design of 2-D IIR filters having quadrantally-symmetric frequency responses, where the transfer functions have separable denominators. In this paper, we propose a weighted least-squares (WLS) design method for 2-D IIR filters having arbitrary frequency response and stable in the practical bounded-input bounded-output (P-BIBO) sense. Our design considers transfer functions with nonseparable numerators and denominators having complex-and real-valued coefficients, respectively. We formulate the WLS design as an iterative second-order cone programming problem, which includes constraints to guarantee the P-BIBO stability. Design examples confirm that the proposed WLS method leads to P-BIBO stable 2-D IIR filters.

Mostly-online teaching experiences in circuits and systems (CAS) during 2020-2021 COVID-19 pandemic are presented. Three case studies are shared summarizing course details, tools and platforms, best practices and limitations across three universities representing different continents. The presented approaches attempt to address several limitations of passive online delivery of CAS courses via interactive simulations, formative assessments via interactive web content and slide-embedded polls, at-home labs with student acquired hardware and instructor-lead and student-centered activity based learning.

A method for acquisition of high bandwidth signals is presented as a typical example of a signal processing application of chromatic derivatives and approximations. Chromatic derivatives are numerically robust differential operators based on orthogonal polynomials. Theoretical formulations required for synthesising an analog chromatic derivative filterbank based on all-pass filters is presented. Such an analog filterbank with N +1 filters can be used for digital acquisition of high bandwidth signals by simultaneously sampling the outputs of the filterbank at a rate 2/(N + 1) of the Nyquist rate, resulting in samples of the signal and higher order chromatic derivatives up to order N, which in turn are used to reconstruct the original signal back. The value of the signal at any instant is obtained from only two nearest samples of the chromatic derivatives filterbank.

Three-dimensional space-time velocity filters may be used to enhance dynamic passband objects of interest in videos while attenuating moving interfering objects based on their velocities. In this paper, we show that the attenuation of interfering stopband objects may be significantly improved using recently proposed shifted-velocity filters. It is shown that an improvement of approximately 20 dB in signal-to-interference ratio may be achieved for stopband to passband velocity differences of only 1 pixels/frame. More importantly, this improvement is achieved without increasing the computational complexity.

We propose a weighted least-squares (WLS) design method for multi-dimensional (M-D) complex-coefficient finite- extent impulse response (FIR) filters. We consider the general form of M-D FIR filters having arbitrary frequency responses and low group delays. We formulate the proposed WLS design as a second-order cone programming problem. Design examples confirm that the proposed method provides the state-of-the-art M-D FIR filter designs with almost constant group delay.

Geometric information of scenes available with four-dimensional (4-D) light fields (LFs) paves the way for post-capture refocusing. Light field refocusing methods proposed so far have been limited to a single planar or a volumetric region of a scene. In this letter, we demonstrate simultaneous refocusing of multiple volumetric regions in LFs. To this end, we employ a 4-D sparse finite-extent impulse response (FIR) filter consisting of multiple hyperfan-shaped passbands. We design the 4-D sparse FIR filter as an optimal filter in the least-squares sense. Experimental results confirm that the proposed filter provides 63% average reduction in computational complexity with negligible degradation in the fidelity of multi-volumetric refocused LFs compared to a 4-D nonsparse FIR filter.

A minimax design for 2-D complex-coefficient FIR filters having asymmetric frequency responses is proposed in this paper. We consider the general form of 2-D FIR filters with low group delay and formulate the minimax design as a semidefinite programming problem. The 2-D linear-phase FIR filters with conjugate-symmetric coefficients are a special case of the proposed design. Example filter designs having near-equiripple magnitude responses are presented to verify the effectiveness of the proposed design method.

A low-complexity codec and a hardware architecture are proposed for achieving real-time compression of four-dimensional (4-D) light field (LF) signals captured from camera/lenslet arrays. The proposed system employs the 4-D extension of the two-dimensional (2-D) 8×8 approximate discrete cosine transform (ADCT) that has recently appeared in the literature. Motivated by the partial separability of the multidimensional spectrum of LFs, the proposed 4-D ADCT is obtained by cascading 2-D inter-view and 2-D intra-view transform stages. Software simulations are provided to confirm the performance of the 4-D ADCT based compression and comparisons are made with respect to 2-D inter-view only and 2-D intra-view only ADCT-based compression. Proposed digital architectures are validated using stepped hardware co-simulation on a Xilinx Virtex-7 VC-707 FPGA platform verifying 597 MHz maximum possible clock frequency, implying an ideal throughput of 18×103LFs/sec for performing 4-D ADCT on (8× 8×432×624×3) size LFs. When 10% of the ADCT coefficients per each (8×8×8×8) hypercube are retained sub aperture images show 38 dB average PSNR and 0.95 average SSIM.

A combined approach of low-complexity light field depth filtering and deep learning is proposed for object classification in the presence of partial occlusions. The proposed approach exploits depth information embedded in multi-perspective four-dimensional (4-D) light fields via low-complexity 4-D sparse depth filtering and deep-learning. The proposed 4-D depth filter, designed using numerical optimization techniques by formulating as an ℓ1- ℓ∞minimization problem, is shown to outperform typical light field refocusing based on 4-D shift-sum averaging filters. Experiments conducted using a light field dataset acquired by a Lytro camera verify 45% and 27% better performance in terms of object classification accuracy compared to the cases when no depth filtering is employed and standard shift-sum refocusing is employed, respectively.

Replay attack refers to the use of recorded speech in an attempt to spoof an automatic speaker verification system and the development of countermeasures that can detect these attacks is an active area of research. This paper investigates the effect of phoneme specific information on replay attack detection. It then develops a replay detection system that employs phoneme specific genuine and spoof models and compares novel scoring methods that take into account phonetic information obtained from a suitable phoneme recogniser. Experiment result on the ASVSpoof 2017 V2.0 corpus indicated that replayed speech may be easier to detect from speech corresponding to some phonemes compared to others and consequently judicious use of phoneme specific models can improve replay detection systems.

A low-complexity wideband transmit beamformer is proposed using a digitally-fed uniform linear array of broadband Vivaldi antennas operating in the S-band. The proposed transmit beamformer employs a novel DSP feeding network based on a transmit-mode 2-D sparse finite-extent impulse response (FIR) filter having a planar passband in the 2-D frequency-wavenumber space. Electronic beam steering is achieved by changing the filter coefficients defined in closed-form and hard-thresholding (HT) is employed to obtain a sparse 2-D impulse responses of the filter. Full-wave electromagnetic simulations are used to obtain the far-field beam patterns produced by the 2-D sparse FIR filter in the frequency range 2-2.8 GHz for wideband signals with 33% fractional bandwidth. Computational complexity, beam directionality and side-lobe performance are investigated with varying HT along with quantitative comparisons with an equally selective wideband frequency-domain phased array.

Application of depth-selective filtering to modulated-sparse light fields towards reducing the DSP and memory complexities in real-time light field processing is investigated. A modulated-sparse light field is obtained by spatially windowing an original 4-D light-field signal, which is subsequently processed by 4-D depth-selective filters to achieve planar focus and occlusion suppression. Multidimensional spectral properties of modulated-sparse light fields are explored and demonstrative examples with real light fields are provided to show that almost similar depth filtering and occlusion suppression performance can be achieved by processing such modulated-sparse light fields, leading to significant reduction in DSP hardware and memory complexities.

The Internet of Things (IoT) is being hailed as the next wave revolutionizing our society, and smart homes, enterprises, and cities are increasingly being equipped with a plethora of IoT devices. Yet, operators of such smart environments may not even be fully aware of their IoT assets, let alone whether each IoT device is functioning properly safe from cyber-attacks. In this paper, we address this challenge by developing a robust framework for IoT device classification using traffic characteristics obtained at the network level. Our contributions are fourfold. First, we instrument a smart environment with 28 different IoT devices spanning cameras, lights, plugs, motion sensors, appliances, and health-monitors. We collect and synthesize traffic traces from this infrastructure for a period of six months, a subset of which we release as open data for the community to use. Second, we present insights into the underlying network traffic characteristics using statistical attributes such as activity cycles, port numbers, signalling patterns, and cipher suites. Third, we develop a multi-stage machine learning based classification algorithm and demonstrate its ability to identify specific IoT devices with over 99 percent accuracy based on their network activity. Finally, we discuss the trade-offs between cost, speed, and performance involved in deploying the classification framework in real-time. Our study paves the way for operators of smart environments to monitor their IoT assets for presence, functionality, and cyber-security without requiring any specialized devices or protocols.

The development of automatic systems that can detect replayed speech has emerged as a significant research challenge for securing voice biometric systems and is the focus of this paper. Specifically, this paper proposes two novel features to capture the static and dynamic characteristics of the signal from the modulation spectrum, which complement short term spectral features for use in replay detection. The modulation spectral centroid frequency feature is proposed as a vector representation of the first order spectral moments of the modulation spectrum. In conjunction to this, the long term spectral average serves to capture the static characteristics of the modulation spectrum. The proposed system, employing a GMM back-end, was evaluated on the ASVSpoof 2017 dataset and found to yield an EER of 6.54%.

Light field signal processing allows manipulation of a rich set of information captured from a scene to achieve real-time depth filtering and occlusion suppression. Low-complexity four-dimensional infinite impulse response digital filters for simultaneous depth filtering and occlusion suppression over multiple depths in light fields are proposed. A low-complexity two-dimensional separable approach is employed to design the proposed filters having multiple frequency-planar pass-bands/stopbands in the four-dimensional spatial frequency domain, that can be electronically tuned to enhance/reject planar objects at multiple depths in a light field. Filter synthesis details are provided with specific design examples corresponding to 2-passband and 1-stopband cases. Numerically generated and Lytro camera captured light fields are used to verify the effectiveness of the proposed multi-depth-pass and multi-depth-reject filters. For synthetic light field inputs these filters confirm an average denoising, depth filtering and occlusion suppression performance of 20 dB, 20 dB, and 30 dB, respectively.

Spoofing detection systems for automatic speaker verification have moved from only modelling voiced frames to modelling all speech frames. Unvoiced speech has been shown to carry information about spoofing attacks and anti-spoofing systems may further benefit by treating voiced and unvoiced speech differently. In this paper, we separate speech into low and high energy frames and independently model the distributions of both to form two spoofing detection systems that are then fused at the score level. Experiments conducted on the ASVspoof 2015, BTAS 2016 and Spoofing and Anti-Spoofing (SAS) corpora demonstrate that the proposed approach of fusing two independent high and low energy spoofing detection systems consistently outperforms the standard approach that does not distinguish between high and low energy frames.

An analog all-pass filter based transfer function synthesis method is proposed for realizing multifunctional microwave active circuits. An analog realization is obtained by replacing unit sample delays in an existing digital prototype with a second-order all-pass analog filter. A novel space time array processor (STAP) and a frequency and bandwidth agile multi-band filter have been simulated using the proposed transfer function synthesis method using measured S- parameters of a fabricated 130 nm second-order CMOS all- pass filter. Simulated array patterns of the STAP beamformer show improved side-lobe performance for better interference suppression and noise rejection. The tunability of the multi-band analog filter, in terms of the center frequency and the quality factor, is verified up to 8 GHz, which has potential applications in analog microwave front-ends.

Design approaches for radio frequency (RF) analog realization of two-dimensional (2-D) network-resonant plane-wave filters are discussed. The plane-wave filters having potential applications in electronically scanned wideband beamforming scenarios operate in spatially-discrete temporally-continuous 2-D mixed-domain as described by their recursive input-output relationships. The proposed approaches imply analog array processing architectures consisting of identical interconnected analog modules (AMs). A 65 nm CMOS circuit simulation of a single AM operating at 700 MHz is used to verify the 2-D plane-wave filter response and array pattern in the first approach. An all-pass filter based time delay approximation is used to design the AMs in the second approach, where a prototype CMOS all-pass filter operating at 5.6 GHz is simulated to verify the 2-D plan-wave filter frequency response and array pattern in closed-form.

In this paper, we present an overview of recent advances in multidimensional (MD) systems and signal processing. We focus on topics closely related to the four papers selected into the special session of “recent advances in multidimensional systems and signal processing” at ISCAS 2015. The paper starts with an overview of the theory of MD IIR digital filters and its applications ranging from image/videos of light-fields to microwave and mm-wave antenna array processing. State-space formulation for the realization of MD IIR notch filters is also discussed as applicable to image processing scenarios. Thereafter, new developments in visual tomography-based imaging systems that exploit MD signal processing towards safety and health applications are discussed. The paper also reviews new theoretical developments in modeling of physical systems. Recent advances in MD Kirchhoff circuit realizations for some physical systems including finite speed heat diffusion are reviewed.

RF-FPGAs and field-programmable filter arrays require tunable analog filters that can be digitally reconfigured in real-time to have several user-selected passbands and stopband notches. Such reconfigurable analog filters must operate in the microwave frequencies up to several GHz in order to meet the needs of emerging cognitive radio and reconfigurable radar front-ends. Tunable passive filters based on RF-MEMS, surface acoustic wave- and planar-technologies have been explored in the recent past to achieve this goal. In this paper, a novel RF-IC approach to design microwave filterbanks having multiple bands, each having independently tunable center frequency and quality factors, is proposed. The proposed technique is based on transfer function synthesis using first-order all-pass filters as a building block. Using measured data from a current-mode 130-nm CMOS allpass filter implementation, the feasibility of multi-band tunable filter arrays is simulated with a tuning range of 4 GHz.

Cognitive radio relies on accurate spectrum sensing for increasing the spectral efficiency of wireless networks. A novel array processing scheme is proposed based on a uniform linear array (ULA) of circularly-polarized spiral antennas having frequency range 2–6 GHz, which is used in conjunction with digital beam filters having 2-D IIR transfer functions for accurately and efficiently placing radio sources in wireless environment. Algorithms such as cyclostationary feature extraction is employed at beamformer to measure energy and realize feature/modulation detection, which in turn allows classification of a wireless environment. Simulation examples are provided for demonstrating the low-complexity directional feature detector with applications towards enhancing access to radio spectrum. Examples showing classification of sources by direction, frequency channels and modulation type in the 2–4 GHz band at SNR=6 dB are given.

A spatially discrete temporally continuous antenna array analog signal processing scheme that can produce highly selective hexagonal beams is proposed. A three dimensional (3-D) infinite impulse response (IIR) filter transfer function having hexagonal beam shaped passbands in the 3-D space-time frequency domain ω is introduced. A hexagonal beam passband in ω produces a hexagonal radio beam in the array pattern, and having closely packed multiple hexagonal beams, one can optimally sense a given sky area in a typical radar/microwave imaging application. The proposed array processing scheme employs analog RF circuits for achieving scaling, summing and time delay as building blocks for the signal processing operation. The 3-D IIR filter transfer function is derived by considering an example 10th-order 1-D Butterworth prototype polynomial.

The application of multi-dimensional (MD) infinite impulse response (IIR) space-time beam filters in radio source localization in cognitive radio (CR) environments is investigated. Knowledge of the position of radio sources in a CR network leads to the detection of white spaces in the MD frequency domain, thereby creating more opportunistic links for the secondary users. The use of MD IIR beam filters is motivated by their very low computational complexity and small side lobe levels compared to digital phased arrays. As a proof-of-concept, the two dimensional (2-D) propagation scenario including at least two receiver stations and a data fusion station, which combines the direction of arrival (DOA) estimates from the two receiver stations, to yield a position estimate, is considered. Each receiver station employs a uniform linear array (ULA) of antennas and a steerable 2-D IIR beam filter and provides information pertaining to peak energy directions. First order 2-D IIR beam filters are shown to provide acceptable DOA estimates with a SNR of 6 dB. The peak energy direction information leads to both position and MD white space detection.

An electronically steerable broadband radio frequency (RF) filter-sum beamforming filter using 1st-order all-pass filters is proposed. The beamforming filter has the 2-D transfer function Ha (zx, sct), which uses M-section cascaded 1st-order all-pass filters and analog combiners as building blocks. Beam steering is achieved by tuning the group delay of the all-pass filters via a control voltage. For beam directions ψ ≤ 20ofrom array broadside, M = 1 provides close to ideal broadband response, and 120°. The array factor of the beamformer is evaluated using 65 nm CMOS BSIM 4 simulations of the all-pass filters and a 4-channel RF combiner for a linear antenna array of 4 antennas and is shown to provide steerable beams at 1 GHz. The CMOS simulations verify a broadband response from DC to 1 GHz.

Industry demand for highly-skilled digital VLSI and embedded systems engineers has made the teaching of design a challenging task for undergraduate educators. Increasingly challenging electronic design automation (EDA) environments call for a variety of skills in engineering graduates which necessitate not only industrial skills but also fundementals in basic science and digital design. These urgent needs are addressed by creating a digital logic design course taught at the freshman level that introduces students to VHDL design of digital VLSI systems while including core concepts. Critical thinking, logic synthesis and circuit innovation take priority over conventional analysis techniques. This case study includes example design projects that have been successfully implemented at The University of Akron.

A two-dimensional (2D) space-time (ST) delay operator D2DST[·] and a novel discrete-space-continuous-time (DSCT) CMOS VLSI implementation at radio frequency (RF) is proposed. The proposed delay operator is able to delay 2D ST antenna array signals along space and time and can be used as a building block in 2D ST array processing algorithms. A 2D non-separable DSCT transfer function (TF), ΦApp(zx, sct) is used to approximate the ideal 2D ST delay represented by the 2D TF equation. A passive frequency planar transformation followed by bilinear transform along spatial dimension is used to derive ΦApp(zx, sct) starting from a 1D passive all-pass prototype. The 2D delay D2DST[·] is proposed to be realized using an array of identical analog modules (AMs). A CMOS VLSI circuit operating at RF is proposed for each AM. Magnitude and phase frequency responses of a single AM operating at 1 GHz is obtained using 65 nm TSMC CMOS simulations in Cadence and compared with the theoretical responses. The 2D phase frequency response of D2DST[·] is obtained using the CMOS simulated response of a single AM.

The potential use of multi-dimensional (MD) signal processing concepts and 1-D tunable bandpass filtering (BPF) for 2-D space-time (ST) spectrum sensing in a cognitive radio environment is proposed. The 2-D ST spectrum sensing allows the secondary users to search and detect white spaces along different spatial directions at a given time instance. This 2-D ST interrogation of the radio environment enables efficient sharing of primary frequency bands over multiple spatial directions in different instances of time. The use of frequency agile antennas is highlighted to mitigate interferences at known frequencies. Broadband/intermediate-frequency (IF) and analog/digital realizations of 2-D ST filters are proposed to perform the directional enhancement of signals. A low complexity highly-selective tunable 1-D digital BPF is proposed to be used with energy detection to perform spectral sensing along the required direction in space. The tunable BPF eliminates the need of computationally intensive high resolution FFT for frequency scanning. A prototype FPGA implementation of the BPF operating at 66 MHz is used to study the effect of finite precision arithmetic with a word length of 8 bits.

A continuous-time discrete-space 2D IIR fan filter is proposed for ultra-wideband beamforming for uniform linear arrays of antennas. The proposed signal-flow-graph replaces sampled unit-delays in a 2D FIR digital prototype fan filter using time-delays of the same duration using an ideal delay line. Thereafter, ideal delays are approximated using an RC-active VLSI circuit consisting of high-order all-pass filters aimed at the 90 nm CMOS technology. The paper covers transfer function design, 2D input spectra in continuous-time, delay approximation, CMOS all-pass circuits and simulation. Finally, a prototype with fan axis directed along θ = 30° (from temporal frequency axis) and half fan angle ε = 6° is simulated and the frequency response from DC to 3.6 GHz is obtained using data from a BSIM4 model of a 10th- order all-pass filter. The proposed novel analog 2D fan filters are free of aliasing, quantization noise, switching power consumption, and do not require an array of high-speed analog-to-digital converters.