20 papers · ranked by Valyu relevance
Varsha Kakkara, Karthi Balasubramanian, B. Yamuna, Deepak Mishra + 3 more
'Karthikeyan Lingasubramanian' 'Senthil Murugan' 'Miriam Leeser'] Integrated circuits may be vulnerable to hardware Trojan attacks during its design or fabrication phases. This article is a case study of the design of a Viterbi decoder and the effect of hardware Trojans on a coded communication system employing the…
Alireza Mohammadidoost, Matin Hashemi
—Many research works have been performed on implementation of Vitrerbi decoding algorithm on GPU instead of FPGA because this platform provides considerable flexibility in addition to great performance. Recently, the recently-introduced Tensor cores in modern GPU architectures provide incredible computing capability.…
Alireza Mohammadidoost, Matin Hashemi
—This paper describes a parallel implementation of Viterbi decoding algorithm. Viterbi decoder is widely used in many state-of-the-art wireless systems. The proposed solution optimizes both throughput and memory usage by applying optimizations such as unified kernel implementation and parallel traceback. Experimental…
Mark Sterling, Hyekyun Rhee, Mark Bocko
The development of an Automated System for Asthma Monitoring (ADAM) is described. This consists of a consumer electronics mobile platform running a custom application. The application acquires an audio signal from an external user-worn microphone connected to the device analog-to-digital converter (microphone input).…
T. Kalavathi Devi, Sakthivel Palaniappan
Convolutional codes are comprehensively used as Forward Error Correction (FEC) codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a…
Rajat Bhattacharjya, Biswadip Maity, Nikil Dutt
Viterbi decoders are widely used in communication systems, natural language processing (NLP), and other domains. While Viterbi decoders are compute-intensive and power-hungry, we can exploit approximations for early design space exploration (DSE) of trade-offs between accuracy, power, and area. We present Locate, a DSE…
Hassan Kilavo, Michael Kisangiri, Salehe I. Mrutu
Viterbi Algorithm Decoder Enhanced with Non-transmittable Codewords is one of the best decoding algorithm which effectively improves forward error correction performance. HoweverViterbi decoder enhanced with NTCs is not yet designed to work in storage media devices. Currently Reed Solomon (RS) Algorithm is almost the…
Zita Abreu, Julia Lieb, Michael Schaller
The classical way of dealing with errors during data transmission over some communication channel have been linear block codes, which are vector spaces over some finite field Fq. Convolutional codes as modules over Fq[z] are a generalization of linear block codes to the polynomial setting. These codes are often used in…
Kallie Whritenour, Mete Civelek, Farzad Farnoud
DNA has been proposed as an alternative to magnetic and solid-state devices for storing digital data. In DNA data storage, writing data is performed through DNA synthesis, and reading is done via sequencing. Nanopore devices for sequencing DNA, like those produced by Oxford Nanopore Technologies, allow long reads and…
Alexey Shapin, Denis Kleyko, Nikita Lyamin, Evgeny Osipov + 1 more
'O.G. Melentyev'] Abstract—The performance of convolutional codes decoding by the Viterbi algorithm should not depend on the particular distribution of zeros and ones in the input messages, as they are linear. However, it was identified that specific implementations of Add-Compare-Select unit for the Viterbi Algorithm…
Waqar Ahmad, Imran Hafeez Abbassi, Usman Sanwal, Hasan Mahmood
—In recent years, the decoding algorithms in communication networks are becoming increasingly complex aiming to achieve high reliability in correctly decoding received messages. These decoding algorithms involve computationally complex operations requiring high performance computing hardware, which are generally…
Piero Fariselli, Pier Luigi Martelli, Rita Casadio
Background Structure prediction of membrane proteins is still a challenging computational problem. Hidden Markov models (HMM) have been successfully applied to the problem of predicting membrane protein topology. In a predictive task, the HMM is endowed with a decoding algorithm in order to assign the most probable…
Moisès Coll Macià, Laurits Skov, Zenia Elise Damgaard Bæk, Asger Hobolth
Insights into the admixture history between modern and archaic humans require accurately inferred introgressed fragments within modern genomes. Here, we introduce two enhancements to hidden Markov models (HMMs) implemented in hmmix. First, we develop a method for sampling hidden state sequences conditional on observed…
Shubham Chandak, Joachim Neu, Kedar Tatwawadi, Jay Mardia + 7 more
As magnetization and semiconductor based storage technologies approach their limits, bio-molecules, such as DNA, have been identified as promising media for future storage systems, due to their high storage density (petabytes/gram) and long-term durability (thousands of years). Furthermore, nanopore DNA sequencing…
Ian Holmes
We describe a strategy for constructing codes for DNA-based information storage by serial composition of weighted finite-state transducers. The resulting state machines can integrate correction of substitution errors; synchronization by interleaving watermark and periodic marker signals; conversion from binary to…
Sajjad Nassirpour, Ilan Shomorony, Alireza Vahid
We study the problem of retrieving data from a channel that breaks the input sequence into a set of unordered fragments of random lengths, which we refer to as the chop-and-shuffle channel. The length of each fragment follows a geometric distribution. We propose nested Varshamov-Tenengolts (VT) codes to recover the…
Joseph G. Makin, David A. Moses, Edward F. Chang
A decade after the first successful attempt to decode speech directly from human brain signals, accuracy and speed remain far below that of natural speech or typing. Here we show how to achieve high accuracy from the electrocorticogram at natural-speech rates, even with few data (on the order of half an hour of spoken…
Jingcheng Zhang, Lei Chen, Jinlin Sun, Shumin Li + 5 more
DNA has emerged as a compelling archival storage medium, offering unprecedented information density and millennia-scale durability. Despite its promise, DNA-based data storage faces critical challenges due to error-prone processes during DNA synthesis, storage, and sequencing. In this study, we introduce Gungnir, a…
Tagir Akhmetshin, Arkadii Lin, Timur Madzhidov, Alexandre Varnek
Autoencoders represent a promising technique for the inverse quantitative structure-activity relationship (QSAR) task. However, undesirable bias, such as atom ordering, affects the neighbourhood behaviour of autoencoders’ latent space and, consequently, usage of the latent vectors as variables in machine-learning…
Victor H. R. Nogueira, Rishabh Sharma, Rafael V. C. Guido, Michael J. Keiser
As efforts to improve the robustness of molecular representations advance, so does the need for methods to test and validate them. We use a Variational Auto-Encoder (VAE), an unsupervised deep learning model, to generate anomalous samples of a well-known molecular string format called SELF-referencIng Embedded Strings…