This paper presents a dynamic adaptation scheme for the frequency of inter-deme migration in distributed genetic algorithms (GA), and its VLSI hardware design. Distributed GA, or multi-deme-based GA, uses multiple populations which evolve concurrently. The purpose of dynamic adaptation is to improve convergence performance so as to obtain better solutions. Through simulation experiments, we pro...

Dynamic rate adaptation for uplink data transmission in a cellular multidimensional multicode (MDMC) direct-sequence code-division multiple-access packet data network is modeled and analyzed in this paper. An analytical framework is developed to evaluate the performances of radio link level dynamic rate adaptation schemes under multipath fading and log-normal shadowing. The radio link level thr...

An auditory model based on zero-crossings with peak amplitudes (ZCPA) was used as a front-end for automatic speech recognition (ASR) with the perceptual property of adaptation as determined by psychoacoustic observations. The model performance was evaluated on the isolated digits (TIDIGITS) database using continuous density HMM recognizer in additive noise. Experimental results indicate that th...

SUMMARY A new approach to speech feature estimation under noise circumstances is proposed in this paper. It is used in noise-robust continuous speech recognition (CSR). As the noise robust techniques in isolated word speech recognition, the running spectrum analysis (RSA), the running spectrum filtering (RSF) and the dynamic range adjustment (DRA) methods have been developed. Among them, only R...

The auditory system operates over a vast range of sound pressure levels (100-120 dB) with nearly constant discrimination ability across most of the range, well exceeding the dynamic range of most auditory neurons (20-40 dB). Dean et al. (2005) have reported that the dynamic range of midbrain auditory neurons adapts to the distribution of sound levels in a continuous, dynamic stimulus by shiftin...

Prolonged adaptation to motion in a given direction produces distinctly different visual motion aftereffects (MAEs) when viewing static vs. dynamic test displays. The dynamic MAE can be exactly simulated by real motion, whereas the static MAE cannot. In addition, the magnitude of the dynamic MAE depends on the bandwidth of motion directions experienced during adaptation, whereas the static MAE ...