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This paper proposes the Two-Valued Symmetric Circulant Matrix (TVSCM), a very sparse architecture that uses only two weights per layer to achieve over 80x parameter reduction on MNIST and MIT-BIH arrhythmia datasets while maintaining comparable accuracy, making it ideal for edge and tiny-ML platforms.