UNDERDETERMINED SIGNAL REPRESENTATION VIA LINEAR PROJECTIONS USING BINARY SPARSE MATRICES- SIGNAL COMPRESSION

This paper presents and studies analytically a new compressive sensing (CS) approach with the aim of bringing this technique closer to successful commercialization in image sensor circuits. Unlike existing CS techniques that use random measurement matrices (RMM) to encode a signal given in form of a vector of discrete samples, the proposed technique utilizes carefully chosen custom measurement matrices. In CS measurement operation, RMM are often used to achieve small coherence between the measurement matrix and the sparse representation bases. However, when applied in practice, RMM based CS designs typically lead to complicated hardware design and thus have a large circuit overhead to obtain random summations. The proposed custom measurement matrix achieves about the same level of incoherence as the RMMs, but results in a dramatically simplified CS measurement circuit, improving both energy efficiency and circuit scalability, and thus the attractiveness of this technique for industrial commercialization. The proposed method is evaluated analytically in terms of Peak Signal to Noise Ratio (PSNR), a measure for the quality of the reconstructed compared to the original signal. Matlab simulations are also conducted to evaluate the effectiveness of the proposed technique, and to compare simulated and estimated PSNRs. Finally, the proposed technique is extended to two-dimensional projections with the aim of further improving signal quality, in particular with high compression rates. A newly formulated minimization problem is proposed to combine the projections in both dimensions to a single optimization problem

Current Compensation Techniques for Low-voltage High-performance Current Mirror Circuits

This paper presents two current mirror circuits for low-voltage applications. Unlike most current mirrors that use stacked transistors in the output branch to boost the output resistance, the proposed designs use current compensation techniques to achieve high output resistance. By avoiding stacked transistors in the output branch, the minimum output voltages of the proposed circuits are significantly lower compared to those of other current mirror circuits with comparable output resistance. Particularly, the first design emphasizes on reducing the minimum output voltage to an extremely low level of around 20mV. The second design stresses minimizing implementation cost. Compared to a simple current mirror circuit, the second design requires only one additional transistor but boosts the output resistance by more than 10 times. Both circuit analysis and simulations are presented to examine the performance of the proposed designs

Digital LDO modelling techniques for performance estimation at early design stage

This work studies the transient responses and steady-state ripples of digital low dropout (LDO) voltage regulators. Simulation models as well as closed-form expressions are provided for estimating the LDO output settling behaviour after load current or reference voltage changes. Estimation equations for the magnitude and frequency of LDO output steady-state ripples are also presented. The accuracy of the developed models is verified by comparing estimation data with results obtained from circuit simulations. The use of the developed estimation equations in design space exploration is also demonstrated

Design of Scalable Hardware-Efficient Compressive Sensing Image Sensors

This work presents a new compressive sensing (CS) measurement method for image sensors, which limits pixel summation within neighbor pixels and follows regular summation patterns. Simulations with a large set of benchmark images show that the proposed method leads to improved image quality. Circuit implementation for the proposed CS measurement method is presented with the use of current mode pixel cells; and the resultant CS image sensor circuit is significantly simpler than existing designs. With compression rates of 4 and 8, the developed CS image sensors can achieve 34.2 dB and 29.6 dB PSNR values with energy consumption of 1.4 mJ and 0.73 mJ per frame, respectively

Design Techniques for Direct Digital Synthesis Circuits with Improved Frequency Accuracy over Wide Frequency Ranges

Recently, there are increasing interests in impedance sensors for various applications. Direct digital synthesis (DDS) circuits are commonly used in such sensor circuits for generating stimulus signals, due to the advantages of accurate frequency control, drift-free performance, etc. Previously reported DDS circuits for sensor applications typically maintain superb frequency accuracy within relatively small frequency ranges. This paper investigates techniques to improve frequency accuracy over wide frequency ranges. In addition, it presents an analytical framework to estimate the signal to noise ratio (SNR) of the generated signal and derives guidelines for optimizing DDS circuit configurations. Both simulation and hardware measurement results are presented to validate the derived SNR estimation equation as well as the developed frequency accuracy enhancement technique

A Probabilistic Fatigue Strength Assessment in AlSi-Cast Material by a Layer-Based Approach

An advanced lightweight design in cast aluminium alloys features complexly shaped geometries with strongly varying local casting process conditions. This affects the local microstructure in terms of porosity grade and secondary dendrite arm spacing distribution. Moreover, complex service loads imply changing local load stress vectors within these components, evoking a wide range of highly stressed volumes within different microstructural properties per load sequence. To superimpose the effects of bulk and surface fatigue strength in relation to the operating load sequence for the aluminium alloy EN AC 46200, a layer-based fatigue assessment concept is applied in this paper considering a non-homogeneous distribution of defects within the investigated samples. The bulk fatigue property is now obtained by a probabilistic evaluation of computed tomography results per investigated layer. Moreover, the effect of clustering defects of computed tomography is studied according to recommendations from the literature, leading to a significant impact in sponge-like porosity layers. The highly stressed volume fatigue model is applied to computed tomography results. The validation procedure leads to a scattering of mean fatigue life from −2.6% to 12.9% for the investigated layers, inheriting strongly varying local casting process conditions

Numerical crack growth study on porosity afflicted cast steel specimens

This paper deals with the fatigue assessment of cast steel defects in terms of macroscopic shrinkage porosity. Within preliminary studies, a generalized Kitagawa diagram GKD was established by numerical analyses of V-notched specimens with varying opening angles. It was experimentally verified by the application of the notch stress intensity factor (NSIF) concept on fatigue tests under rotating bending and axial loading. This paper continuous the work by an application of the GKD to real cast steel pores. At first, casting simulations are performed to design representative cast specimen geometries. The study focusses on macroscopic shrinkage pores with different spatial shapes. At second, fatigue tests under axial loading are conducted. Subsequent fracture surface analysis by light optical and scanning electron microscopy provides fracture mechanical based geometry parameters. Finally, the results of the experiments related to the failure relevant defect sizes are assessed by the GKD. In order to define an equivalent defect size of the complexly shaped defects, numerical crack growth analyses are performed demonstrating crack coalescence path tendencies. Summing up, the application of the NSIF approach based on a GKD shows a sound accordance to the experimental results and thus provides an engineering-feasible fatigue assessment method of cast steel components with macroscopic imperfections

The role of individual compensation and acceptance decisions in crowdsourced delivery

High demand, rising customer expectations, and government regulations are forcing companies to increase the efficiency and sustainability of urban (last-mile) distribution. Consequently, several new delivery concepts have been proposed that increase flexibility for customers and other stakeholders. One of these innovations is crowdsourced delivery, where deliveries are made by occasional drivers who wish to utilize their surplus resources (unused transport capacity) by making deliveries in exchange for some compensation. In addition to reducing delivery costs, the potential benefits of crowdsourced delivery include better utilization of transport capacity, a reduction in overall traffic, and increased flexibility (by scaling up and down delivery capacity as needed). The use of occasional drivers poses new challenges because (unlike traditional couriers) neither their availability nor their behavior in accepting delivery offers is certain. The relationship between the compensation offered to occasional drivers and the probability that they will accept a task has been largely neglected in the scientific literature. Therefore, we consider a setting in which compensation-dependent acceptance probabilities are explicitly considered in the process of assigning delivery tasks to occasional drivers. We propose a mixed-integer nonlinear model that minimizes the expected delivery costs while identifying optimal assignments of tasks to a mix of traditional and occasional drivers and their compensation. We propose exact linearization schemes for two practically relevant probability functions and an approximate linearization scheme for the general case. The results of our computational study show clear advantages of our new approach over existing ones

In-medium Hadrons - Properties, Interaction and Formation

In this talk various aspects of in-medium behavior of hadrons are discussed with an emphasis on observable effects. Examples for theoretical predictions of in-medium spectral functions are given and the importance of resonance-hole excitations is stressed. It is also stressed that final state interactions can have a major effect on observables and thus have to be considered as part of the theory. This is demonstrated with examples from neutrino-nucleus interactions. Finally, the possibility to access hadron formation times in high-energy photonuclear (or neutrino-induced) reactions is illustrated.Comment: Invited talk given by U. Mosel at Vth Conference on Hadronic Physics, ICTP, Trieste, May 200