Downloads provided by UsageCounts
The focus of this paper is on classification of different vehicles using sound emanated from the vehicles. In this paper,quadratic discriminant analysis classifies audio signals of passing vehicles to bus, car, motor, and truck categories based on features such as short time energy, average zero cross rate, and pitch frequency of periodic segments of signals. Simulation results show that just by considering high energy feature vectors, better classification accuracy can be achieved due to the correspondence of low energy regions with noises of the background. To separate these elements, short time energy and average zero cross rate are used simultaneously.In our method,we have used a few features which are easy to be calculated in time domain and enable practical implementation of efficient classifier. Although, the computation complexity is low, the classification accuracy is comparable with other classification methods based on long feature vectors reported in literature for this problem.
FOS: Computer and information sciences, Classification accuracy, Sound (cs.SD), Quadratic Discriminant Analysis, Computer Science - Sound, Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Short time analysis., Separation criterion, Electrical Engineering and Systems Science - Audio and Speech Processing, Periodic segments
FOS: Computer and information sciences, Classification accuracy, Sound (cs.SD), Quadratic Discriminant Analysis, Computer Science - Sound, Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Short time analysis., Separation criterion, Electrical Engineering and Systems Science - Audio and Speech Processing, Periodic segments
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 4 | |
| downloads | 5 |

Views provided by UsageCounts
Downloads provided by UsageCounts