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Microbial Fuel Cell (MFC) power production and Microbial Electrolysis Cell (MEC) organic production depend strongly on their dynamic environment conditions, like inlet substrate concentration, temperature, etc. This work presents a discrete extremum seeking controller to quickly tune the MFC and MEC electrical settings in order to achieve maximum performance irrespective of these dynamic environment...
This work presents an 8 – 11b resolution scalable and energy efficient ADC, using the oversampled and noise shaping SAR architecture in 90nm UMC CMOS process. Further, the proposed ADC simplifies the design of the noise shaping filter to enable the use of a first order switched capacitor low pass filter for shaping the comparator noise and the in band quantization noise. The ADC design alleviates...
Several applications in machine learning and machine-to-human interactions tolerate small deviations in their computations. Digital systems can exploit this fault-tolerance to increase their energy-efficiency, which is crucial in embedded applications. Hence, this paper introduces a new means of Approximate Computing: Dynamic-Voltage-Accuracy-Frequency-Scaling (DVAFS), a circuit-level technique enabling...
The Phoenix1 project aims to develop a new approach to explore unknown environments, based on multiple measurement campaigns carried out by extremely tiny devices, called agents, that gather data through multiple sensors. These low power and low resource agents are configured specifically for each measurement campaign to achieve the exploration goal in the smallest number of iterations. Thus, the...
This forum brings together experts in software applications, system architectures, and chip designs to explore cognitive computing approaches over the near-, mid-, and long-term.
ConvNets, or Convolutional Neural Networks (CNN), are state-of-the-art classification algorithms, achieving near-human performance in visual recognition [1]. New trends such as augmented reality demand always-on visual processing in wearable devices. Yet, advanced ConvNets achieving high recognition rates are too expensive in terms of energy as they require substantial data movement and billions of...
Wireless acuusuc sensor networks (wasns) are a promising technology for performing acoustic surveillance because of their flexibility and low cost. However, their commercialization is nowadays limited due to their high energy consumption, which is mainly a result of the high data rates required to stream audio data between sensor nodes. In order to improve energy efficiency in WASNs, we explore the...
Analog-to-information converters and Compressed Sampling (CS) sensor front-ends try to only extract the relevant, information-bearing elements of an incoming data stream. Information extraction and recognition tasks can run directly on the compressed data stream without needing full signal reconstruction. The accuracy of the extracted information or classification is strongly determined by the front-end...
An ultra-low power adaptive sampling controller is presented for online data reduction in low power ECG systems. The proposed adaptive sampling controller dynamically adapts the sampling frequency to enables high quality acquisition of QRS complexes in ECG signals for accurate heartbeat detection and heart rate variability analysis at significantly reduced average sampling rate. To compensate for...
State-of-the-art solutions to optical flow fail to jointly offer high density flow estimation, low power consumption and real time operation, rendering them unsuitable for embedded applications. Joint hardware-software scalability at run-time is crucial to achieve these conflicting requirements in one device. This paper therefore presents a scalable Lucas-Kanade optical flow algorithm, together with...
3D interposers are one of just a few ways of making electronic systems faster and more powerful, but their design can be complex. This paper presents a optimization flow to assist the design of silicon interposers with the highest bandwidth density possible. Using the methodology described in this paper, simulations have shown that chip-to-chip links on a silicon interposer can achieve bandwidth densities...
A low-power precision-scalable processor for ConvNets or convolutional neural networks (CNN) is implemented in a 40nm technology. Its 256 parallel processing units achieve a peak 102GOPS running at 204MHz. To minimize energy consumption while maintaining throughput, this works is the first to both exploit the sparsity of convolutions and to implement dynamic precision-scalability enabling supply-...
Filter-banks based on a gm-C topology are popular in acoustic sensor systems targeting spectral analysis. Their benefits lie in a very low power consumption and center-frequency scalability through gm-tuning to cover the audio frequency range. However the linear signal swing at the output of the filter is limited due to the inherent non-linearity of the input transistors in a differential pair. This...
Recently convolutional neural networks (ConvNets) have come up as state-of-the-art classification and detection algorithms, achieving near-human performance in visual detection. However, ConvNet algorithms are typically very computation and memory intensive. In order to be able to embed ConvNet-based classification into wearable platforms and embedded systems such as smartphones or ubiquitous electronics...
Smart energy management, both at design time and at run time, is indispensable in modern radios. It requires a careful trade-off between the system’s performance, and its power consumption. Moreover, the design has to be dynamically reconfigurable to optimally balance these parameters at run time, depending on the current operating conditions. Energy Scalable Radio Design starts by describing an...
Heart rate (HR) and its variability (HRV) provide critical information about an individual's cardiovascular and mental health state. In either application, long-term observation is crucial to arrive at conclusive decisions and provide useful diagnostic feedback [1]. Photoplethysmographic (PPG) estimation of HR and HRV has emerged as an attractive alternative to ECG, as it provides electrode-free operation...
The densification of wireless networks that contend for a shared medium, demands improved MAC solutions that can reduce the energy cost of packet collisions. In this paper we analyze a novel in-band full duplex collision and interference detection scheme for dense networks, studying the energy savings that it can bring with respect to the performance of half duplex communications. Under a high external...
Hardware security in server, client, mobile and embedded systems is becoming increasingly critical, especially with the rapid growth of the Internetof- Everything (IoE). Security threats and vulnerabilities for all hardware components must be addressed. This forum brings together chip designers and system architects to discuss: (1) design, hardware and logistics attack challenges, as well as advanced...
Processors targeting embedded perception and cognition have evolved tremendously in the past decade. CMOS process scaling continues to provide reductions in area and energy consumption. This makes it feasible to equip next generation processing with human-like intelligence for emerging applications such as gesture detection, object recognition, and classification.
This paper presents a thorough assessment of the impact redundancy has on background calibration performance in SAR ADCs with static and dynamic non-idealities. A configurable model that is capable of implementing different SAR architectures is used to inject various implementation impairments and and analyze the impact redundancy has on them. The effects of a redundant capacitor array on calibration...
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