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New control technique could improve accuracy of industrial robots

Researchers have developed a new feedforward method that improves on conventional techniques by obtaining parameters from an uncertain environment. This approach achieved better performance than the traditional method in simulations, and is set to be tried out on industrial robots and machine vision.

Why, sometimes, we don't see what we actually saw

Researchers found that the brain's inability to process information quickly enough can lead to a bottleneck in visual processing, resulting in missed stimuli. By reducing interference between feedforward and feedback signals, they observed improved detection and categorization performance.

How does the brain make perceptual predictions over time?

Neuroscientist David Heeger proposes a new theory that explains how the brain uses prediction and inference to make decisions. The brain's neural network can process sensory input in a feedforward manner, but also runs in a feedback mode to generate predictions, and combines both modes for optimal performance.

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Finding a better way to quiet noisy environments

A new mathematical algorithm designed to improve noise cancellation technologies can reduce unwanted helicopter and cabin noise by 40 decibels or more. The 'feedforward' active-noise control works by generating anti-noise signals that adapt to acoustic coupling, solving a long-standing problem in the field.