The　automatic　musical　instrument　classification　has　many　applications　such　as　music　information　retrieval,　music　reconstruction　and　audio　classification.　In　this　paper,　wind　instrumental　music　and　bowstring　instrumental　music　are　studied　based　on　the　database　consisting　of　2896　clips　from　8　different　classes　of　musical　instruments　(horn,　clarinet,　oboe,　trumpet,　cello,　viola,　violin,　and　doublebass).　With　audio　features　including　spectral　centroid,　spectral　spread,　low　energy　frame　ratio,　Mel-Frequency　Cepstral　Coefficients,　formant　frequency　interval,　and　fundamental　frequency,　classification　using　Support　Vector　Machine　whose　parameters　are　optimized　by　Particle　Swarm　Optimization　searching　algorithm,　gives　an　accuracy　of　92.22%,　the　accuracy　is　close　to　or　better　than　the　ones　reported　on　the　similar　data　sets　and　using　other　classifiers.　©　2012　Springer-Verlag　GmbH.