14 papers · ranked by Valyu relevance
Nur Ahmadi, Timothy G. Constandinou, Christos-Savvas Bouganis
Robustness and decoding accuracy remain major challenges in the clinical translation of intracortical brain-machine interface (BMI) systems. In this work, we show that a signal/decoder co-design methodology (exploiting the synergism between the input signal and decoding algorithm within the design development process)…
Liyan Liang, Qian Zhang, Jie Zhou, Wenyu Li + 2 more
Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems have been extensively researched over the past two decades, and multiple sets of standard datasets have been published and widely used. However, there are differences in sample distribution and collection equipment across…
Kevin D. Volkel, Paul W. Hook, Albert Keung, Winston Timp + 1 more
As nanopore technology reaches ever higher throughput and accuracy, it becomes an increasingly viable candidate for reading out DNA data storage. Nanopore sequencing offers considerable flexibility by allowing long reads, real-time signal analysis, and the ability to read both DNA and RNA. We need flexible and…
Zhicheng Liu, Liuquan Yao, Shuai Yuan, Guiying Yan + 5 more
'Yuting Liu' 'Yanlin Geng' 'Youlong Wu' 'Ling Liu'] In this paper, we propose the threshold successive cancellation flip (Th-SCF) decoding algorithm for polar codes, which enhances the performance of the SC decoder while maintaining low complexity. Theoretical analysis reveals that Th-SCF asymptotically delays the…
Xiumin Wang, Jinlong He, Jun Li, Liang Shan
A traditional successive cancellation (SC) decoding algorithm produces error propagation in the decoding process. In order to improve the SC decoding performance, it is important to solve the error propagation. In this paper, we propose a new algorithm combining reinforcement learning and SC flip (SCF) decoding of…
Sho Nakagome, Trieu Phat Luu, Yongtian He, Akshay Sujatha Ravindran + 1 more
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline decoding analysis with different models and conditions to assess how they…
Matthew R Whiteway, Bruno Averbeck, Daniel A Butts
Decoding is a powerful approach for measuring the information contained in the activity of neural populations. As a result, decoding analyses are now used across a wide range of model organisms and experimental paradigms. However, typical analyses employ general purpose decoding algorithms that do not explicitly take…
Axel Andersson, Ferran Diego, Fred A. Hamprecht, Carolina Wählby
In Situ Transcriptomics (IST) is a set of image-based transcriptomics approaches that enables localisation of gene expression directly in tissue samples. IST techniques produce multiplexed image series in which fluorescent spots are either present or absent across imaging rounds and colour channels. A spot’s presence…
Niklas Gassner, Julia Lieb, Abhinaba Mazumder, Michael Schaller
In this paper, we present a framework for generic decoding of convolutional codes, which allows us to do cryptanalysis of code-based systems that use convolutional codes as public keys. We then apply this framework to information set decoding, study success probabilities and give tools to choose variables. Finally, we…
Mingkang Li, Ruixue Wang, Guihua Wan, Yuqi Yang + 1 more
Calcium imaging has gained extensive application in neural decoding tasks because of its high precision in observing cortical neural activity. Nevertheless, the immense data volume and complexity of automated signal extraction algorithms in calcium imaging result in significant delays in extracting neuronal calcium…
Nima Maleki, Hamid Karimi-Rouzbahani
Sensory neural coding, the brain’s process of transforming inputs into informative patterns of neural activity, generates complex and multiplexed neural codes which are hard to interpret. Although decoding methods have facilitated the interpretation of these codes, the specific features of neural activity that…
R. Jabakhanji, A.D. Vigotsky, J. Bielefeld, L. Huang + 3 more
High-profile studies claim to assess mental states across individuals using multi-voxel decoders of brain activity. The fixed, fine-grained, multi-voxel patterns in these “optimized” decoders are purportedly necessary for discriminating between, and accurately identifying, mental states. Here, we present compelling…
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…
Tomasz Krokosz, Jarogniew Rykowski, Małgorzata Zajęcka, Robert Brzoza-Woch + 2 more
'Robert Brzoza-Woch' 'Leszek Rutkowski' 'Amitabh Mishra'] Modern, commonly used cryptosystems based on encryption keys require that the length of the stream of encrypted data is approximately the length of the key or longer. In practice, this approach unnecessarily complicates strong encryption of very short messages…