Density Evolution for Deterministic Generalized Product Codes with Higher-Order Modulation

Generalized product codes (GPCs) are extensions of product codes (PCs) where coded bits are protected by two component codes but not necessarily arranged in a rectangular array. It has recently been shown that there exists a large class of deterministic GPCs (including, e.g., irregular PCs, half-product codes, staircase codes, and certain braided codes) for which the asymptotic performance under iterative bounded-distance decoding over the binary erasure channel (BEC) can be rigorously characterized in terms of a density evolution analysis. In this paper, the analysis is extended to the case where transmission takes place over parallel BECs with different erasure probabilities. We use this model to predict the code performance in a coded modulation setup with higher-order signal constellations. We also discuss the design of the bit mapper that determines the allocation of the coded bits to the modulation bits of the signal constellation.Comment: invited and accepted paper for the special session "Recent Advances in Coding for Higher Order Modulation" at the International Symposium on Turbo Codes & Iterative Information Processing, Brest, France, 201

Deterministic and Ensemble-Based Spatially-Coupled Product Codes

Several authors have proposed spatially-coupled (or convolutional-like) variants of product codes (PCs). In this paper, we focus on a parametrized family of generalized PCs that recovers some of these codes (e.g., staircase and block-wise braided codes) as special cases and study the iterative decoding performance over the binary erasure channel. Even though our code construction is deterministic (and not based on a randomized ensemble), we show that it is still possible to rigorously derive the density evolution (DE) equations that govern the asymptotic performance. The obtained DE equations are then compared to those for a related spatially-coupled PC ensemble. In particular, we show that there exists a family of (deterministic) braided codes that follows the same DE equation as the ensemble, for any spatial length and coupling width.Comment: accepted at ISIT 2016, Barcelona, Spai

Pruning Neural Belief Propagation Decoders

We consider near maximum-likelihood (ML) decoding of short linear block codes based on neural belief propagation (BP) decoding recently introduced by Nachmani et al.. While this method significantly outperforms conventional BP decoding, the underlying parity-check matrix may still limit the overall performance. In this paper, we introduce a method to tailor an overcomplete parity-check matrix to (neural) BP decoding using machine learning. We consider the weights in the Tanner graph as an indication of the importance of the connected check nodes (CNs) to decoding and use them to prune unimportant CNs. As the pruning is not tied over iterations, the final decoder uses a different parity-check matrix in each iteration. For Reed-Muller and short low-density parity-check codes, we achieve performance within 0.27 dB and 1.5 dB of the ML performance while reducing the complexity of the decoder

VIRD: Immersive Match Video Analysis for High-Performance Badminton Coaching

Badminton is a fast-paced sport that requires a strategic combination of spatial, temporal, and technical tactics. To gain a competitive edge at high-level competitions, badminton professionals frequently analyze match videos to gain insights and develop game strategies. However, the current process for analyzing matches is time-consuming and relies heavily on manual note-taking, due to the lack of automatic data collection and appropriate visualization tools. As a result, there is a gap in effectively analyzing matches and communicating insights among badminton coaches and players. This work proposes an end-to-end immersive match analysis pipeline designed in close collaboration with badminton professionals, including Olympic and national coaches and players. We present VIRD, a VR Bird (i.e., shuttle) immersive analysis tool, that supports interactive badminton game analysis in an immersive environment based on 3D reconstructed game views of the match video. We propose a top-down analytic workflow that allows users to seamlessly move from a high-level match overview to a detailed game view of individual rallies and shots, using situated 3D visualizations and video. We collect 3D spatial and dynamic shot data and player poses with computer vision models and visualize them in VR. Through immersive visualizations, coaches can interactively analyze situated spatial data (player positions, poses, and shot trajectories) with flexible viewpoints while navigating between shots and rallies effectively with embodied interaction. We evaluated the usefulness of VIRD with Olympic and national-level coaches and players in real matches. Results show that immersive analytics supports effective badminton match analysis with reduced context-switching costs and enhances spatial understanding with a high sense of presence.Comment: To Appear in IEEE Transactions on Visualization and Computer Graphics (IEEE VIS), 202

A receptor-like kinase mutant with absent endodermal diffusion barrier displays selective nutrient homeostasis defects

We thank the Genomic Technologies Facility (GTF) and the Central Imaging Facility (CIF) of the University of Lausanne for expert technical support. We thank Valérie Dénervaud Tendon, Guillaume Germion, Deborah Mühlemann, and Kayo Konishi for technical assistance and John Danku and Véronique Vacchina for ICP-MS analysis. This work was funded by grants from the Swiss National Science Foundation (SNSF), the European Research Council (ERC) to NG and a Human Frontiers Science Program (HFSP) grant to JT and NG. GL and CM were supported by the Agropolis foundation (Rhizopolis) and the Agence Nationale de la Recherche (HydroRoot; ANR-11-BSV6-018). MB was supported by a EMBO long-term postdoctoral fellowship, JEMV by a Marie Curie IEF fellowship and TK by the Japan Society for the Promotion of Sciences (JSPS).Peer reviewedPublisher PD

Probabilistic Synapses

Learning, especially rapid learning, is critical for survival. However, learning is hard: a large number of synaptic weights must be set based on noisy, often ambiguous, sensory information. In such a high-noise regime, keeping track of probability distributions over weights - not just point estimates - is the optimal strategy. Here we hypothesize that synapses take that optimal strategy: they do not store just the mean weight; they also store their degree of uncertainty - in essence, they put error bars on the weights. They then use that uncertainty to adjust their learning rates, with higher uncertainty resulting in higher learning rates. We also make a second, independent, hypothesis: synapses communicate their uncertainty by linking it to variability, with more uncertainty leading to more variability. More concretely, the value of a synaptic weight at a given time is a sample from its probability distribution. These two hypotheses cast synaptic plasticity as a problem of Bayesian inference, and thus provide a normative view of learning. They are consistent with known learning rules, offer an explanation for the large variability in the size of post-synaptic potentials, and make several falsifiable experimental predictions

On Low-Complexity Decoding of Product Codes for High-Throughput Fiber-Optic Systems

We study low-complexity iterative decoding algorithms for product codes. We revisit two algorithms recently proposed by the authors based on bounded distance decoding (BDD) of the component codes that improve the performance of conventional iterative BDD (iBDD). We then propose a novel decoding algorithm that is based on generalized minimum distance decoding of the component codes. The proposed algorithm closes over 50% of the performance gap between iBDD and turbo product decoding (TPD) based on the Chase-Pyndiah algorithm at a bit error rate of 10^-5. Moreover, the algorithm only leads to a limited increase in complexity with respect to iBDD and has significantly lower complexity than TPD. The studied algorithms are particularly interesting for high-throughput fiberoptic communications

Test 1157: John Deere 2630 and 2640 Diesel

EXPLANATION OF TEST REPORT GENERAL CONDITIONS East tractor is a production model equipped for common usage. Power consuming accessories can be disconnected only when it is convenient for the operator to do so in practice. Additional weight can be added as ballast if the manufacturer regularly supplies it for sale. The static tire loads and the inflation pressures muse conform to recommendations in the Tire Standards published by the Society of Automotive Engineers. PREPARATION FOR PERFORMANCE RUNS The engine crank case is drained and refilled with a measured amount of new oil conforming to specifications in the operator’s manual. The fuel used and the maintenance operations must also conform to the published information delivered with the tractor. The tractor is then limbered-up for 1 hour on drawbar work in accordance with the manufacturers published recommendations. The manufacturer’s representative is present to make appropriate decisions regarding mechanical adjustments. The tractor is equipped with approximately the amount of added ballast that is used during maximum drawbar tests. The tire tread-bar height must be at least 65% of new tread height prior to the maximum power run. BELT OR POWER TAKE-OFF PERFORMANCE Maximum Power and Fuel Consumption. The manufacturer’s representative makes carburetor, fuel pump, ignition and governor control settings which remain unchanged throughout tall subsequent runs. The governor and the manually operated governor control lever is set to provide the high-idle speed specified by the manufacturer for maximum power. Maximum power is measured by connecting the belt pulley or the power take-off to a dynamometer. The dynamometer load is then gradually increased until the engine is operating at the rated speed specified by the manufacturer for maximum power. The corresponding fuel consumption is measured. Varying Power and Fuel Consumption. Six different horsepower levels are used to show corresponding fuel consumption rates and how the governor causes the engine to react to the following changes in dynamometer load: 85% of the dynamometer torque at maximum power; minimum dynamometer torque, ½ the 85% torque; maximum power; ¼ and ¾ of the 85% torque. Since at tractor is generally subjected to varying loads the average of the results in this test serve well for predicting the fuel consumption of a tractor in general usage. DRAWBAR PERFORMANCE All engine adjustments are the same as those used in the belt or power take-off tests. If the manufacturer specifies a different rated crankshaft speed for drawbar operations, then the position of the manually operated governor control is changed to provide the high-idle speed specified by the manufacturer in the operating instructions. Varying Power and Fuel Consumption With Ballast. The varying power runs are made to show the effect of speed-control devices (engine governor, automatic transmissions, etc.) on horsepower, speed and fuel consumption. These runs are made around the entire test course with has two 180 degree turns with a minimum radius of 50 feet. The drawbar pull is set at 3 different levels as follows: (1) as near to the pull a maximum power as possible and still have the tractor maintain the travel speed at maximum horsepower on the straight sections of the test course; (2) 75% of the pull at maximum power; and (3) 50% of the pull at maximum power. Prior to 1958, fuel consumption data (10 hour test) were shown only for the pull obtained at maximum power for tractors having torque converters and at 75% of the pull obtained at maximum power for gear-type tractors. Maximum Power With Ballast. Maximum power is measured on straight level sections of the test course. Data are shown for not more that 12 different gears or travel speeds. Some gears or travel speeds may be omitted because of high slippage of the traction members or because the travel speed may exceed the safe-limit for the test course. The maximum safe speed for the Nebraska Test course has been set at 15 miles per hour. The slippage limits have been set at 15% and 7% for pneumatic tires and steel tracks or lugs, respectively. Higher slippage gives widely varying results. Maximum Power Without Ballast. All added ballast is removed from the tractor. The maximum drawbar power of the tractor is determined by the same procedure used for getting maximum power with ballast. The gear (or travel speed) is the same as that used in the 10-hours test. Varying Power and Travel Speed With Ballast. Travel speeds corresponding to drawbar pulls beyond the maximum power range are obtained to show the “lugging ability” of the tractor. The run starts with the pull at maximum power; then additional drawbar pull is applied to cause decreasing speeds. The run is ended by one of three conditions; (1) maximum pull is obtained, (2) the maximum slippage limit is reached, or (3) some other operating limit is reached