Searched for: subject%3A%22quantization%22
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van der Noort, Rover (author)
Edge AI is an architectural deployment tactic that brings AI models closer to the user and data, relieving internet bandwidth usage and providing low latency and privacy. It remains unclear how this tactic performs at scale, since the distribution overhead could impact the total energy consumption. We identify four architectural scalability...
master thesis 2024
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Li, Qiongxiu (author), Gundersen, Jaron Skovsted (author), Lopuhaa-Zwakenberg, Milan (author), Heusdens, R. (author)
Privacy-preserving distributed average consensus has received significant attention recently due to its wide applicability. Based on the achieved performances, existing approaches can be broadly classified into perfect accuracy-prioritized approaches such as secure multiparty computation (SMPC), and worst-case privacy-prioritized approaches...
journal article 2024
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Safaei, Mohammad (author), Hejazian, Mahsa (author), Pedrammehr, Siamak (author), Pakzad, Sajjad (author), Ettefagh, Mir Mohammad (author), Fotouhi, M. (author)
Gantry cranes play a pivotal role in various industrial applications, and their reliable operation is paramount. While routine inspections are standard practice, certain defects, particularly in less accessible components, remain challenging to detect early. In this study, first a finite element model is presented, and the damage is introduced...
journal article 2024
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Magri, Federico (author)
In this study, we present a first step towards a cutting-edge software framework that will enable autonomous racing capabilities for nano drones. Through the integration of neural networks tailored for real-time operation on resource-constrained devices. A lightweight Convolutional Neural Network, with the Gatenet architecture, is adjusted for...
master thesis 2023
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Sochirca, Dan (author)
Code generation models have become more popular recently, due to the fact that they assist developers in writing code in a more productive manner. While these large models deliver impressive performance, they require significant computational resources and memory, making them difficult to deploy and expensive to train. Additionally, their large...
bachelor thesis 2023
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Lv, Maolong (author), De Schutter, B.H.K. (author), Cao, Jinde (author), Baldi, S. (author)
Practical tracking results have been reported in the literature for high-order odd-rational-power nonlinear dynamics (a chain of integrators whose power is the ratio of odd integers). Asymptotic tracking remains an open problem for such dynamics. This note gives a positive answer to this problem in the framework of prescribed performance...
journal article 2023
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Jiang, Longxing (author), Aledo Ortega, D. (author), van Leuken, T.G.R.M. (author)
Logarithmic quantization for Convolutional Neural Networks (CNN): a) fits well typical weights and activation distributions, and b) allows the replacement of the multiplication operation by a shift operation that can be implemented with fewer hardware resources. We propose a new quantization method named Jumping Log Quantization (JLQ). The key...
conference paper 2023
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Eland, E.N. (author), Mehrotra, Shubham (author), Karmakar, S. (author), van Veldhoven, Robert (author), Makinwa, K.A.A. (author)
Zoom ADCs combine a coarse SAR ADC with a fine delta-sigma modulator (?SM) to efficiently obtain high energy efficiency and high dynamic range. This makes them well suited for use in various instrumentation and audio applications. However, zoom ADCs also have drawbacks. The use of over-ranging in their fine modulators may limit SNDR, large...
book chapter 2023
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Zhang, H. (author), Berkhout, M. (author), Makinwa, K.A.A. (author), Fan, Q. (author)
This article presents a digital-input class-D amplifier (CDA) achieving high dynamic range (DR) by employing a chopped capacitive feedback network and a capacitive digital-to-analog converter (DAC). Compared with conventional resistive-feedback CDAs driven by resistive or current-steering DACs, the proposed architecture eliminates the noise...
journal article 2023
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Jiang, Longxing (author)
Convolutional Neural Networks (CNN) have become a popular solution for computer vision problems. However, due to the high data volumes and intensive computation involved in CNNs, deploying CNNs on low-power hardware systems is still challenging.<br/>The power consumption of CNNs can be prohibitive in the most common implementation platforms:...
master thesis 2022
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Li, Qiongxiu (author), Heusdens, R. (author), Christensen, M.T. (author)
Privacy issues and communication cost are both major concerns in distributed optimization in networks. There is often a trade-off between them because the encryption methods used for privacy-preservation often require expensive communication overhead. To address these issues, we, in this paper, propose a quantization-based approach to achieve...
journal article 2022
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Kleijweg, Zep (author)
The recently introduced posit number system was designed as a replacement for IEEE 754 floating point, to alleviate some of its shortcomings. As the number distribution of posits is similar to the data distributions in deep neural networks (DNNs), posits offer a good alternative to fixed point numbers in DNNs: using posits can result in high...
master thesis 2021
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Draškić, Radoica (author)
Superconducting quantum circuits came out as promising candidates for the exploration of topological phenomena that are currently inaccessible in condensed<br/>matter systems. One such circuit is a Cooper pair transistor which has already<br/>been widely studied in different regimes of operation due to its importance in<br/>quantum computation....
master thesis 2021
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Eland, E.N. (author), Karmakar, S. (author), Gonen, B. (author), van Veldhoven, Robert (author), Makinwa, K.A.A. (author)
This article describes a discrete-time zoom analog-to-digital converter (ADC) intended for audio applications. It uses a coarse 5-bit SAR ADC in tandem with a fine third-order delta-sigma modulator (ΔΣM) to efficiently obtain a high dynamic range. To minimize its over-sampling ratio (OSR) and, thus, its digital power consumption, the...
journal article 2021
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Kieft, Bas (author)
The most widely applied feedback controller is PID. This controller gains its popularity because of the ease of design through loop shaping, since PID can be analyzed in the frequency domain. However, PID is limited by linearity. Reset control is a nonlinear addition to PID control. Through linearization techniques it can be designed by...
master thesis 2020
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Zhang, J. (author)
In speech processing applications, e.g., speech recognition, hearing aids (HAs), video conferencing, and human-computer interaction, speech enhancement or noise reduction is an essential front-end task, as the recorded speech signals are inevitably corrupted by interference, including coherent/incoherent noise and reverberation. Traditional...
doctoral thesis 2020
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Lv, Maolong (author), Yu, Wenwu (author), Cao, Jinde (author), Baldi, S. (author)
This work investigates the consensus tracking problem for high-power nonlinear multiagent systems with partially unknown control directions. The main challenge of considering such dynamics lies in the fact that their linearized dynamics contain uncontrollable modes, making the standard backstepping technique fail; also, the presence of mixed...
journal article 2020
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Fan, Xiangyu (author), Bai, Peng (author), Huanyu, L. I. (author), Deng, Xiongfeng (author), Lv, Maolong (author)
In this paper, the finite-time tracking control problem of a class of multi-agent systems with nonaffine functions and uncertain nonlinearity is investigated, which is different from the existing on high-order multi-agent systems with pure feedback forms. The multi-agent systems considered in this paper, moreover, the nonaffine functions and...
journal article 2020
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Zhu, B. (author), Al-Ars, Z. (author), Hofstee, H.P. (author)
Binary Convolutional Neural Networks (CNNs) have significantly reduced the number of arithmetic operations and the size of memory storage needed for CNNs, which makes their deployment on mobile and embedded systems more feasible. However, after binarization, the CNN architecture has to be redesigned and refined significantly due to two reasons:...
conference paper 2020
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Overwater, Ramon (author)
The quantum bits (qubits) at the core of any quantum computers are so fragile that quantum error correction(QEC) schemes are needed to increase their robustness and enable fault-tolerant quantum algorithms. The surface code is one of the most popular QEC schemes, but it requires the availability of an efficient decoder. While neural networks...
master thesis 2019
Searched for: subject%3A%22quantization%22
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