Related papers: Analog Circuit Sizing Using Machine Learning Based…
We present the design and performance of a prototype ASIC digitizer for integrated wire chamber readout, implemented in 65 nm commercial CMOS technology. Each channel of the 4-channel prototype is composed of two 16-bit Time-to-Digital…
The past several years have witnessed the success of transformer-based models, and their scale and application scenarios continue to grow aggressively. The current landscape of transformer models is increasingly diverse: the model size…
We propose a technique to assist in converting a reference layout of an analog circuit into the procedural layout generator by efficiently reusing available generators for sub-cell creation. The proposed convolutional neural network (CNN)…
Accurate and efficient circuit behavior modeling is a cornerstone of modern electronic design automation. Among different types of circuits, stiff circuits are challenging to model using previous frameworks. In this work, we propose a new…
A crucial limit to measurement efficiencies of superconducting circuits comes from losses involved when coupling to an external quantum amplifier. Here, we realize a device circumventing this problem by directly embedding a two-level…
The on-chip implementation of learning algorithms would speed-up the training of neural networks in crossbar arrays. The circuit level design and implementation of backpropagation algorithm using gradient descent operation for neural…
The memristor, because of its controllability over a wide dynamic range of resistance, has emerged as a promising device for data storage and analog computation. A major challenge is the accurate measurement of memristance over a wide…
Protecting superconducting quantum circuits from non-ideal return loss, including out-of-band circulator behavior and enhancing the performance of broadband quantum-limited amplifiers can be accomplished using a superconducting version of a…
Approximate computing (AC) leverages the inherent error resilience and is used in many big-data applications from various domains such as multimedia, computer vision, signal processing, and machine learning to improve systems performance…
Linearity is an important and frequently sought property in electronics and instrumentation. Here, we report a method capable of, given a transfer function, identifying the respective most linear region of operation with a fixed width. This…
This paper investigates the impact of technological constraints on passive elements in the design of inductively degenerated CMOS low-noise amplifiers (LNAs). A theoretical analysis is combined with circuit simulations in a 130-nm CMOS…
To demonstrate supremacy of quantum computing, increasingly large-scale superconducting quantum computing chips are being designed and fabricated. However, the complexity of simulating quantum systems poses a significant challenge to…
During the last years, Graphene based Field Effect Transistors (GFET) have shown outstanding RF performance; therefore, they have attracted considerable attention from the electronic devices and circuits communities. At the same time,…
Analog/mixed-signal circuit design encounters significant challenges due to performance degradation from process, voltage, and temperature (PVT) variations. To achieve commercial-grade reliability, iterative manual design revisions and…
This paper presents an efficient multi-fidelity Bayesian optimization approach for analog circuit synthesis. The proposed method can significantly reduce the overall computational cost by fusing the simple but potentially inaccurate…
Superconducting qubits are a leading platform for scalable quantum computing and quantum error correction. One feature of this platform is the ability to perform projective measurements orders of magnitude more quickly than qubit…
While numerous obfuscation techniques are available for securing digital assets in the digital domain, there has been a notable lack of focus on protecting Intellectual Property (IP) in the analog domain. This is primarily due to the…
In this paper a CMOS operational amplifier is presented which operates at 2V power supply and 1microA input bias current at 0.8 micron technology using non conventional mode of operation of MOS transistors and whose input is depended on…
We present a sub-Nyquist analog-to-digital converter of wideband inputs. Our circuit realizes the recently proposed modulated wideband converter, which is a flexible platform for sampling signals according to their actual bandwidth…
Analog computing based on memristor technology is a promising solution to accelerating the inference phase of deep neural networks (DNNs). A fundamental problem is to map an arbitrary matrix to a memristor crossbar array (MCA) while…