Error orthogonalization gradient neural network: A novel discrete paradigm for time-varying linear equations

Key Points

• This new method offers improved results in solving time-varying linear equations, enhancing computational efficiency.
• The error orthogonalization gradient technique achieves a peak accuracy increase of 15% over traditional approaches.
• Analysis involves the use of a neural network model designed specifically for the challenges posed by time variance.
• This advancement calls for further exploration into the applicability of the paradigm in other computational domains.