19 papers · ranked by Valyu relevance
Kiyoshiro Okada, Katsuhiro Endo, Kenji Yasuoka, Shuichi Kurabayashi + 1 more
'Sheetal Kalyani'] Pseudo-random number generators (PRNGs) are software algorithms generating a sequence of numbers approximating the properties of random numbers. They are critical components in many information systems that require unpredictable and nonarbitrary behaviors, such as parameter configuration in machine…
Ishani Ganguly, Emily L. Heckman, Ashok Litwin-Kumar, E. Josephine Clowney + 1 more
'E. Josephine Clowney' 'Rudy Behnia'] The arthropod mushroom body is well-studied as an expansion layer representing olfactory stimuli and linking them to contingent events. However, 8% of mushroom body Kenyon cells in Drosophila melanogaster receive predominantly visual input, and their function remains unclear. Here…
Steven A. Frank
Organisms perceive their environment and respond. The origin of perception-response traits presents a puzzle. Perception provides no value without response. Response requires perception. Recent advances in machine learning may provide a solution. A randomly connected network creates a reservoir of perceptive…
Jacob Hammond
Random number generation is a key technology that is useful in a variety of ways. Random numbers are often used to generate keys for data encryption. Random numbers generated at a sufficiently long length can encrypt sensitive data and make it difficult for another computer or person to decrypt the data. Other uses for…
Steven A. Frank, Antonio M. Scarfone, Pavel Kraikivski
Organisms perceive their environment and respond. The origin of perception-response traits presents a puzzle. Perception provides no value without response. Response requires perception. Recent advances in machine learning may provide a solution. A randomly connected network creates a reservoir of perceptive…
Stefan Kutschera, Wilhelm Zugaj, Wolfgang Slany
—We aim to access entropy sources available within smartphones in order to construct and evaluate a random number generator which is competitive in comparison with existing and proven random number generators. A prototype utilizing the herein proposed algorithm shall generate data that can be tested against the…
Stefan Kutschera, Wolfgang Slany, Patrick Ratschiller, Sarina Gursch + 2 more
Privacy and security require not only strong algorithms but also reliable and readily available sources of randomness. To tackle this problem, one of the causes of single-event upsets is the utilization of a non-deterministic entropy source, specifically ultra-high energy cosmic rays. An adapted prototype based on…
Jinxin Zhang, Meng Wu, Omprakash Kaiwartya
The key system serves as a vital foundation for ensuring the security of information systems. In the presence of a large scale of heterogeneous sensors, the use of low-quality keys directly impacts the security of data and user privacy within the sensor network. Therefore, the demand for high-quality keys cannot be…
José R. Hurtado, SueYeon Chung, André A. Fenton
The mammalian brain processes experience-dependent spatial information through poorly-understood network mechanisms thought to depend on particular network connectivity patterns and activity-dependent synaptic plasticity. However, dedicated input connections that learn to shape information about place cannot easily…
Francesca Mastrogiuseppe, Joana Carmona, Christian K. Machens
The geometrical and statistical properties of brain activity depend on the way neurons connect together to form recurrent circuits. How the structure of connectivity shapes the emergent activity remains however not fully understood. We investigate this question in recurrent neural networks with additive stochastic…
Raed Abu Zitar, Muhammed J. Al-Muhammed, Chakchai So-In
This paper proposes a hybrid technique for data security. The computational model of the technique is grounded on both the non-linearity of neural network manipulations and the effective distortion operations. To accomplish this, a two-layer feedforward neural network is trained for each plaintext block. The first…
Gilson Wirth, Pedro A. B. Alves, Roberto da Silva
— Generating streams of true random numbers is a critical component of many embedded systems. The design of fully integrated, area and power efficient True Random Number Generators is a challenge. We propose a fully integrated, lightweight implementation, that uses the random telegraph noise (RTN) of standard MOSFET as…
Hojong Choi, Seung-Hyeok Shin, Diego Martín, Masoud Kaveh + 1 more
'Mohammad Reza Mosavi'] Ultrasound systems have been widely used for consultation; however, they are susceptible to cyberattacks. Such ultrasound systems use random bits to protect patient information, which is vital to the stability of information-protecting systems used in ultrasound machines. The stability of the…
Thomas Lynn, Julio Ottino, Richard Lueptow, Paul Umbanhowar
Cut-and-shuffle mixing is an instructive candidate system with which to assess the potential of machine learning (ML) as an approach to solve difficult mixing problems. We focus on a specific subset of cut-and-shuffle systems, the one-dimensional interval exchange transform. This class of mixing operations is well…
Ali Abdolrahimi Zarnagh, Ali Motazedifard
Generating reliable random and pseudo-random sequences is important in many electronic and signal processing systems, such as secure communications, radar, spread-spectrum methods, and autonomous platforms. Although true and quantum random number generators provide stronger unpredictability, classical pseudo-random…
Troy Criss, Ahmed Sidi El Valli, Naomi Li, Andrew Haas + 1 more
We demonstrate a method to generate application-ready truly random bits from a magnetic tunnel junction driven by a Field-Programmable Gate Array (FPGA). We implement a real-time feedback loop that stabilizes the switching probability near 50% and apply an XOR operation, both on the FPGA, to suppress short-term…
Jianan Wu, Ahmad Jamal Salim, Eslam Elmitwalli, Selçuk Köse + 1 more
Programmable Statistics Authors: ['Jianan Wu' 'Ahmad Jamal Salim' 'Eslam Elmitwalli' 'Selçuk Köse' 'Zeljko Ignjatovic'] Abstract—Pseudo-random number generators (PRNGs) are essential in a wide range of applications, from cryptography to statistical simulations and optimization algorithms. While uniform randomness is…
Cecilia Jarne, Ryeongkyung Yoon, Tahra Eissa, Zachary P. Kilpatrick + 1 more
How do recurrent neural networks (RNNs) internally represent elapsed time to initiate responses after learned delays? To address this question, we trained RNNs on delayed decision-making tasks with progressively increasing temporal demands, including binary decisions, context-dependent decisions, and perceptual…
Authors not listed
Solving optimization problems, especially for nonlinear and constrained systems, is a challenge. Decades of specialized algorithms have been developed for general and special cases of root finding, minimization (including constraints), for parameter estimation, and mapping connected spaces. These approaches typically…