Ashok K. Krishnamurthy

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The intensity-weighted average of instantaneous frequency (IWAIF) is developed as a model to predict listener performance in tasks primarily requiring frequency discrimination. IWAIF is closely related to the envelope weighted average of instantaneous frequency (EWAIF) model proposed by Feth for similar tasks. The primary difference is that the IWAIF model(More)
This study evaluates the performance of the multilayer-perceptron and the frequency-sensitive competitive learning network in identifying five commercial aircraft from radar backscatter measurements. The performance of the neural network classifiers is compared with that of the nearest-neighbor and maximum-likelihood classifiers. Our results indicate that(More)
We present a framework for the estimation of driver behavior at intersections, with applications to autonomous driving and vehicle safety. The framework is based on modeling the driver behavior and vehicle dynamics as a hybrid-state system (HSS), with driver decisions being modeled as a discrete-state system and the vehicle dynamics modeled as a(More)
The authors compare the Y. Linde, A. Buzo, and R.M. Gray vector quantization algorithm (1980) with the frequency-sensitive competitive learning neural network. Each of these techniques is applied to two images, and the distortion and SNR are measured for various size codebooks. The results show that the neural network technique of designing codebooks yields(More)
This work focuses on incorporating the LF-model 1] into closed-phase inverse ltering based estimation of glottal source waveforms. The LF-model is a ve-parameter model representing the eeective voice source over open and closed glottal phases. Three techniques for LF-model tting are described: two based on Prony's method and one using gradient descent. The(More)