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The Frequency Distribution Of Quantization Error In Digitizers For Coherent Sampling, Sol Neeman Ph.D.
The Frequency Distribution Of Quantization Error In Digitizers For Coherent Sampling, Sol Neeman Ph.D.
Engineering Studies Faculty Publications and Creative Works
In this paper the frequency distribution of quantization error in coherent sampling of digitizers will be investigated. As the distribution of the quantization error affects the values of THD and SNR, it is relevant for a correct interpretation of THD and SNR of sine waves in coherent sampling. The distribution of the quantization error will be analyzed as a function of N, total number of samples and M, number of cycles in the sample set and it will be proved that for certain cases, the quantization error falls on odd harmonics only of the frequency of the sampled sine wave.
Combining Wavelets And Hotelling Transforms In Image Query, Sol Neeman Ph.D.
Combining Wavelets And Hotelling Transforms In Image Query, Sol Neeman Ph.D.
Engineering Studies Faculty Publications and Creative Works
In the "content based" image query, also referred to as "query by example," "similarity retrieval" or "sketch retrieval," the query image is provided by the user either as a sketch of the object, as the output of a scanner or a video camera. Some of the difficulties associated with content based image query are described in [1], e.g. significant difference between the "query image" and the "target image," artifacts and poor resolution of the query image make a straightforward comparison of images using L1 and l2 metrics not effective.
In [2] a new strategy is suggested based on wavelet decomposition …
Incorporating Matlab's Signal Processing Toolbox Into A Dsp Course At An Undergraduate E.E. Program, Sol Neeman Ph.D.
Incorporating Matlab's Signal Processing Toolbox Into A Dsp Course At An Undergraduate E.E. Program, Sol Neeman Ph.D.
Engineering Studies Faculty Publications and Creative Works
This paper provides some suggestions for incorporating MATLAB's Signal Processing Toolbox into a DSP course. Often, in a DSP course, students have difficulties understanding abstract and non-intuitive concepts and seeing their relevance to the practical part of their curriculum. The tools offered by MATLAB's Signal Processing Toolbox, can help to make these concepts more tangible and provide a perspective for students. Some basic tools relevant to an undergraduate DSP course will be introduced, including examples of tool use and graphic results. The tools presented will be applied in the areas of synthesis and analysis of signals, FFT computation, impulse response …