23 papers · ranked by Valyu relevance
Dennis Yeung, Francesco Negro, Ivan Vujaklija
Neural interfacing via decomposition of high-density surface electromyography (HD-sEMG) should be robust to signal non-stationarities incurred by changes in joint pose and contraction intensity. We present an adaptive real-time motor unit (MU) decoding algorithm and test it on HD-sEMG collected from the extensor carpi…
Alireza Tasdighi, Mansoor Yousefi, Jun Chen
Weighted belief propagation (WBP) for the decoding of linear block codes is considered. In WBP, the Tanner graph of the code is unrolled with respect to the iterations of the belief propagation decoder. Then, weights are assigned to the edges of the resulting recurrent network and optimized offline using a training…
Mehdi Adibi, James S. McDonald, Colin W. G. Clifford, Ehsan Arabzadeh + 1 more
'Ehsan Arabzadeh' 'Olaf Sporns'] Sensory information is encoded in the response of neuronal populations. How might this information be decoded by downstream neurons? Here we analyzed the responses of simultaneously recorded barrel cortex neurons to sinusoidal vibrations of varying amplitudes preceded by three adapting…
Pavithra Rajeswaran, Alexandre Payeur, Guillaume Lajoie, Amy L. Orsborn
Task errors are used to learn and refine motor skills. We investigated how task assistance influences learned neural representations using Brain-Computer Interfaces (BCIs), which map neural activity into movement via a decoder. We analyzed motor cortex activity as monkeys practiced BCI with a decoder that adapted to…
Shizhe Wu, Kinkini Bhadra, Anne-Lise Giraud, Silvia Marchesotti + 1 more
'Ateke Goshvarpour'] Brain-Computer Interfaces (BCIs) aim to establish a pathway between the brain and an external device without the involvement of the motor system, relying exclusively on neural signals. Such systems have the potential to provide a means of communication for patients who have lost the ability to…
Shiva Kumar Planjery, Bane Vasić, David Declercq
—Finite alphabet iterative decoders (FAIDs) for LDPC codes were recently shown to be capable of surpassing the Belief Propagation (BP) decoder in the error floor region on the Binary Symmetric channel (BSC). More recently, the technique of decimation which involves fixing the values of certain bits during decoding, was…
Wiktor Młynarski, Ann M. Hermundstad
The ability to adapt to changes in stimulus statistics is a hallmark of sensory systems. Here, we develop a theoretical framework that can account for the dynamics of adaptation from an information-processing perspective. We use this framework to optimize and analyze adaptive sensory codes, and we show that codes…
Xiumin Wang, Jinlong He, Jun Li, Zhuoting Wu + 2 more
Although the adaptive successive cancellation list (AD-SCL) algorithm and the segmented-CRC adaptive successive cancellation list (SCAD-SCL) algorithm based on the cyclic redundancy check (CRC) can greatly reduce the computational complexity of the successive cancellation list (SCL) algorithm, these two algorithms…
Shizhe Wu, Kinkini Bhadra, Anne-Lise Giraud, Silvia Marchesotti
Brain-Computer Interfaces (BCI) aim to establish a pathway between the brain and an external device without the involvement of the motor system, relying exclusively on neural signals. Such systems have the potential to provide a means of communication for patients who have lost the ability to speak due to a…
Yansong Lv, Hang Yin, Zhanxin Yang, Yuhuan Wang + 2 more
'T. Aaron Gulliver'] Designing an efficient decoder is an effective way to improve the performance of polar codes with limited code length. List flip decoders have received attention due to their good performance trade-off between list decoders and flip decoders. In particular, the newly proposed dynamic successive…
Hao Wang, Wei Zhang, Yanyan Chang, Jiajing Gao + 2 more
'Jerry D. Gibson'] A novel time-varying channel adaptive low-complexity chase (LCC) algorithm with low redundancy is proposed, where only the necessary number of test vectors (TVs) are generated and key equations are calculated according to the channel evaluation to reduce the decoding complexity. The algorithm…
Tilo Strutz, Roman Rischke
—The transmission or storage of signals typically involves data compression. The final processing step in compression systems is generally an entropy coding stage, which converts symbols into a bit stream based on their probability distribution. A distinct class of entropy coding methods operates not by mapping input…
Shinichi Yamagiwa, Yuma Ichinomiya, Stefania Perri
Video applications have become one of the major services in the engineering field, which are implemented by server-client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for security. Recently, the majority of video encoding mechanisms to reduce…
Marcos Faúndez-Zanuy, Oscar Oliva-Suarez
Many speech coders are based on linear prediction coding (LPC), nevertheless with LPC is not possible to model the nonlinearities present in the speech signal. Because of this there is a growing interest for nonlinear techniques. In this paper we discuss ADPCM schemes with a nonlinear predictor based on neural nets…
Qiong Wu, Fan Zhang, Hao Wang, Jun Lin + 1 more
—The Alternating Direction Method of Multipliers (ADMM) decoding of Low Density Parity Check (LDPC) codes has received many attentions due to its excellent performance at the error floor region. In this paper, we develop a parameter-free decoder based on Linear Program (LP) decoding by replacing the binary constraint…
Mitchell Wasson, Mario Miličević, Stark C. Draper, Glenn Gulak
—In this paper we present an FPGA-based implementation of linear programming (LP) decoding. LP decoding frames error correction as an optimization problem. This is in contrast to variants of belief propagation (BP) decoding that view error correction as a problem of graphical inference. There are many advantages to…
Zhihao Lan, WanZhen Liang
The variational quantum eigensolver (VQE) algorithm can simulate the chemical systems such as molecules in the noisy intermediate-scale quantum devices and shows promising applications in quantum chemistry simulations. The accuracy and computational cost of the VQE simulations are determined by the underlying Ansätze.…
Finlay Clark, Graeme Robb, Daniel Cole, Julien Michel
Alchemical absolute binding free energy (ABFE) calculations have substantial potential in drug discovery, but are often prohibitively computationally expensive. To unlock their potential, efficient automated ABFE workflows are required to reduce both computational cost and human intervention. We present a…
Janus Heide, Morten V. Pedersen, Frank H. P. Fitzek, Muriel Médard
—Random Linear Network Coding (RLNC) provides a theoretically efficient method for coding. Some of its practical drawbacks are the complexity of decoding and the overhead due to the coding vectors. For computationally weak and battery-driven platforms, these challenges are particular important. In this work, we…
Jia Lu, Ryan Tsoi, Nan Luo, Yuanchi Ha + 8 more
Dynamical systems often generate distinct outputs according to different initial conditions, and one can infer the corresponding input configuration given an output. This property captures the essence of information encoding and decoding. Here, we demonstrate the use of self-organized patterns, combined with machine…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Guido D'Alessandro, Marcos Faúndez-Zanuy, Francesco Piazza
This paper focuses on a newly developed transparent nADPCMBMLT speech coding algorithm. Our coder first decomposes the narrowband speech signal in subbands, a non linear ADPCM scheme is then performed in each subband. The signal subband decomposition is piloted by the equivalent Modulated Lapped Transform (MLT) filter…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…