The paper introduces TSLANet, a novel lightweight model designed for time series analysis, addressing the limitations of Transformer-based models in handling noise, computational efficiency, and overfitting with smaller datasets. TSLANet combines convolutional operations with adaptive spectral analysis, featuring an Adaptive Spectral Block (ASB) and an Interactive Convolution Block (ICB). The ASB uses Fourier analysis to enhance feature representation by capturing both long-term and short-term interactions while mitigating noise through adaptive thresholding. The ICB refines the model's capacity to decode complex temporal patterns using different kernel sizes. The model is evaluated on various tasks, including classification, forecasting, and anomaly detection, demonstrating superior performance compared to state-of-the-art models. TSLANet's effectiveness is highlighted in its ability to maintain high accuracy levels in noisy conditions and across different data sizes, making it a robust foundation model for time series analysis.The paper introduces TSLANet, a novel lightweight model designed for time series analysis, addressing the limitations of Transformer-based models in handling noise, computational efficiency, and overfitting with smaller datasets. TSLANet combines convolutional operations with adaptive spectral analysis, featuring an Adaptive Spectral Block (ASB) and an Interactive Convolution Block (ICB). The ASB uses Fourier analysis to enhance feature representation by capturing both long-term and short-term interactions while mitigating noise through adaptive thresholding. The ICB refines the model's capacity to decode complex temporal patterns using different kernel sizes. The model is evaluated on various tasks, including classification, forecasting, and anomaly detection, demonstrating superior performance compared to state-of-the-art models. TSLANet's effectiveness is highlighted in its ability to maintain high accuracy levels in noisy conditions and across different data sizes, making it a robust foundation model for time series analysis.