deteriorates rapidly at low Signal-to-Noise Ratios (SNR). To counteract noise uncertainty, a new entropy-based spectrum sensing scheme is introduced in this letter. The entropy of the sensed signal is estimated in the frequency domain with a probability space partitioned into fixed dimensions. It is proven

. Subjects were asked to perform a sequence of everyday tasks but not told specifically where or how to do them. Mean, energy, frequency-domain entropy, and correlation of acceleration data was calculated and several classifiers using these features were tested. Decision tree classifiers showed the best

entropy deconvolution with

A new measure for assessing camera focusing via recorded image is presented in this paper. The proposed measure bases on calculating entropy in image frequency domain, and we call it frequency domain entropy or FDE. First an intuitive explanation of measure is presented, and next tests for some

Lyshevski, Sergey and Krueger, Frank, "Robust entropy-enhanced frequency-domain genomic analysis under uncertainties " (2004).

of the body. Acceleration data was collected from twenty subjects in both laboratory and semi-naturalistic environments. For semi-naturalistic data, subjects were asked to perform a sequence of everyday tasks outside of the laboratory. Mean, energy, frequency-domain entropy, and correlation of acceleration

-forming liquids with the peak frequency decreasesing as the temperature is lowered consistently with the Vogel-Fulcher law with a critical temperature remarkably close to the known critical temperature Tc of the model where the configurational entropy vanishes. PACS: 64.40.-i, 64.60.Cn, 75.10.Nr The spectral

of generalized overlapped block transform (LOT) and 3 types of biorthonormal discrete wavelets transform (OWT). We found by extensive computer simulation on IRLS representative test-images, type and order of transform in the most efficient scalar quantized-entropy coder in each set for compression ratio from 10

-mean. The notion of circular stutionarity is introduced. For the class of proper complex random processes, a discrete Fourier transform correspondence is derived relating circular stationarity in the time domain to uncorrelatedness in the frequency domain. As an application of the theory, the capacity of a

of the sequences have been made using the Approximate Entropy, repeating the same procedure for nine distinct time-frequency distributions. The possibility of classifying correctly the AF episodes depends directly on the selected time-frequency distribution. 1.