ADC Multi-Site Test Based on a Pre-test with Digital Input Stimulus

This paper describes two novel algorithms based on the time-modulo reconstruction method intended for detection of the parametric faults in analogue-to-digital converters (ADC). In both algorithms, a pulse signal, in its slightly adapted form to allow sufficient time for converter settling, is taken as the test stimulus relieving the burden placed on the accuracy requirement of the excitation source. Instead of calculating the accurate conventional dynamic and static parameters, a signature result is obtained through the analysis of the output data in the time domain. The basic concept of the algorithms is the evaluation on the performance of ADCs by the comparison of the similarity of the output waveforms. The multi-site test is expensive for traditional specification-based tests of ADCs, as high quality analogue data generators are required. Based on these two algorithms, this paper proposes a solution for this problem. The objective of the test scheme is not to completely replace traditional specification-based tests, but to provide a reliable method for early identification of excessive parameter variations in production test that allows quickly discarding of most of the faulty circuits before performing a conventional test. The efficiency of the methods is validated on an industrial 12-bit pipelined ADC both in simulations and in measurements.     

Incremental augmented complex adaptive IIR algorithm for training widely linear ARMA model

In this paper, we propose a distributed adaptive learning algorithm to train the coefficients of a widely linear autoregressive moving average model by measurements collected by the nodes of a network. We assume that each node uses the augmented complex adaptive infinite impulse response (ACA-IIR) filter as the learning rule, and nodes interact with each other under an incremental mode of cooperation. To derive the proposed algorithm, called the incremental ACAIIR (IACA-IIR), we firstly formulate the distributed adaptive learning problem as an unconstrained minimization problem. Then, we apply stochastic gradient optimization argument to solve it and derive the proposed algorithm. We further find the step size range where the stability of the proposed algorithm is guaranteed. We also introduce a reduced-complexity version of the IACA-IIR algorithm. Since the proposed algorithm relies on the augmented complex statistics, it can be used to model both types of complex-valued signals (proper and improper signals). To evaluate the performance of the proposed algorithm, we use both synthetic and real-world complex signals in our simulations. The results exhibit superior performance of the proposed algorithm over the non-cooperative ACA-IIR algorithm.     

Shallow and Undoped Germanium Quantum Wells: A Playground for Spin and Hybrid Quantum Technology

Buried‐channel semiconductor heterostructures are an archetype material platform for the fabrication of gated semiconductor quantum devices. Sharp confinement potential is obtained by positioning the channel near the surface; however, nearby surface states degrade the electrical properties of the starting material. Here, a 2D hole gas of high mobility (5 × 10⁵ cm² V^?1 s^?1) is demonstrated in a very shallow strained germanium (Ge) channel, which is located only 22 nm below the surface. The top‐gate of a dopant‐less field effect transistor controls the channel carrier density confined in an undoped Ge/SiGe heterostructure with reduced background contamination, sharp interfaces, and high uniformity. The high mobility leads to mean free paths ≈ 6 µm, setting new benchmarks for holes in shallow field effect transistors. The high mobility, along with a percolation density of 1.2 × 10¹¹cm^?2, light effective mass (0.09m_e), and high effective g‐factor (up to 9.2) highlight the potential of undoped Ge/SiGe as a low‐disorder material platform for hybrid quantum technologies.     

A Noisy Channel Tolerant Image Encryption Scheme

In this paper, we present an image encryption scheme that has the capability to tolerate noisy effects of a wireless channel. This means if the encrypted image data is corrupted by channel noise up to a certain level, correct decryption is possible with some distortion. The proposed image encryption scheme relies on some very interesting properties of orthogonal matrices containing columns that form a set of orthonormal basis vectors. Besides being tolerant to noisy channels, the proposed scheme also provides good security against well-known cryptographic attacks as demonstrated in this paper by a number of experimental results and security analysis.     

On the mechanics of functional asymmetry in bipedal walking

This paper uses two symmetrical models, the passive compass-gait biped and a five-link 3-D biped, to computationally investigate the cause and function of gait asymmetry. We show that for a range of slope angles during passive 2-D walking and mass distributions during controlled 3-D walking, these models have asymmetric walking patterns between the left and right legs due to the phenomenon of spontaneous symmetry-breaking. In both cases a stable asymmetric family of gaits emerges from a symmetric family of gaits as the total energy increases (e.g., fast speeds). The ground reaction forces of each leg reflect different roles, roughly corresponding to support, propulsion, and motion control as proposed by the hypothesis of functional asymmetry in able-bodied human walking. These results suggest that body mechanics, independent of neurophysiological mechanisms such as leg dominance, may contribute to able-bodied gait asymmetry.     

Low-power CMOS distributed amplifier using new cascade gain cell for high and low gain modes

A CMOS distributed amplifier (DA) with low-power and flat and high power gain (S₂₁) is presented. In order to decrease noise figure (NF) an RL terminating network used for the gate transmission line instead of single resistance. Besides, a flat and high S₂₁ is achieved by using the proposed cascade gain cell consist of a cascode-stage with bandwidth extension capacitor. In the high-gain mode, under operation condition of V _dd  = 1.2 V and the overall current consumption of 7.8 mA, simulation result shown that the DA consumed 9.4 mW and achieved a flat and high S₂₁ of 20.5 ± 0.5 dB with an average NF of 6.5 dB over the 11 GHz band of interest, one of the best reported flat gain performances for a CMOS UWB DA. In the low-gain mode, the DA achieved average S₂₁ of 15.5 ± 0.25 dB and an average NF of 6.6 dB with low power consumption (P_DC) of 3.6 mW, the lowest P_DC ever reported for a CMOS DA or LNA with an average gain better than 10 dB.     

Unleashing the Potential of Sodium-Ion Batteries: Current State and Future Directions for Sustainable Energy Storage

Rechargeable sodium-ion batteries (SIBs) are emerging as a viable alternative to lithium-ion battery (LIB) technology, as their raw materials are economical, geographically abundant (unlike lithium), and less toxic. The matured LIB technology contributes significantly to digital civilization, from mobile electronic devices to zero electric-vehicle emissions. However, with the increasing reliance on renewable energy sources and the anticipated integration of high-energy-density batteries into the grid, concerns have arisen regarding the sustainability of lithium due to its limited availability and consequent price escalations. In this context, SIBs have gained attention as a potential energy storage alternative, benefiting from the abundance of sodium and sharing electrochemical characteristics similar to LIBs. Furthermore, high-entropy chemistry has emerged as a new paradigm, promising to enhance energy density and accelerate advancements in battery technology to meet the growing energy demands. This review uncovers the fundamentals, current progress, and the views on the future of SIB technologies, with a discussion focused on the design of novel materials. The crucial factors, such as morphology, crystal defects, and doping, that can tune electrochemistry, which should inspire young researchers in battery technology to identify and work on challenging research problems, are also reviewed.     

Cramer–Rao bound and minimum variance unbiased estimator for joint sampling clock offset and channel taps in MC‐CDMA systems

Exact closed‐form expressions of the Cramer–Rao bound (CRB) for joint sampling clock offset and channel taps are obtained in multi‐carrier code division multiple access systems. CRB is undoubtedly the most well known variance's bound to determine. It provides a benchmark against which we can compare the performance of any unbiased estimator. Furthermore, minimum variance unbiased (MVU) estimator for these parameters is proposed. Moreover, maximum likelihood (ML) and least‐squares estimators for joint sampling clock offset and channel taps are presented. Best linear unbiased estimator is also introduced just for channel taps. The performances of the estimators are compared through simulation results with the proposed CRB. Our results show the better performances of MVU and ML estimators with more computational complexity compared with the others. Copyright © 2008 John Wiley & Sons, Ltd.