Corrigendum to “Morphological dictionary learning based sparse classification for small electric motor state recognition under unbalanced samples” [Appl. Acoust. 227 (2025) 110253] (Applied Acoustics (2025) 227, (S0003682X24004043), (10.1016/j.apacoust.2024.110253))

There is a need to standardize the formatting of certain figure names in the original submission, as described below: Fig. 2. (a) sample of small electric motors and (b) test platform. Fig. 3. Time domain waveforms and spectrum of the small electric motor at different states. (a) time domain waveform and (b) spectrum. Fig. 6. Test results of different data augmentation methods. (a) adding background noise, (b) pitch shifting, (c) time stretching and (d) combined augmentation. Fig. 7. Augment audio samples with combined augmentation. (a) original samples and (b) synthetic samples. Fig. 10. Waveforms after operator processing of Q3 samples. (a) raw, (b) erosion and (c) dilation. Fig. 15. Sparse code contributions for different health states for three test samples. (a) Q1, (b) Q2 and (c) Q3. (D₁, D₂ and D₃ denotes the class-specific sub-dictionary corresponding to Q1, Q2 and Q3, respectively.) The authors would like to apologise for any inconvenience caused.