Mean Squared Error Analysis of Quantizers With Error Feedback
نویسندگان
چکیده
منابع مشابه
Polar coordinate quantizers that minimize mean-squared error
A quantizer for complex data is defined by a partition of the complex plane and a representation point associated with each cell of the partition. A polar coordinate quantizer independently quantizes the magnitude and phase angle of complex data. We derive design equations for minimum mean-squared error polar coordinate quantizers and report some interesting theoretical results on their perform...
متن کاملRoot Mean Squared Error
• Predictive Accuracy Measures. These measures evaluate how close the recommender system came to predicting actual rating/utility values. • Classification Accuracy Measures. These measures evaluate the frequency with which a recommender system makes correct/incorrect decisions regarding items. • Rank Accuracy Measures. These measures evaluate the correctness of the ordering of items performed b...
متن کاملRate-Distortion Analysis of Quantizers with Error Feedback
A ∆Σ modulator that is often utilized to convert analog signals into digital signals can be modeled as a static uniform quantizer with an error feedback filter. In this paper, we present a rate-distortion analysis of quantizers with error feedback including the ∆Σ modulators, assuming that the error owing to overloading in the static quantizer is negligible. We demonstrate that the amplitude re...
متن کاملCompetitive Mean-Squared Error Beamforming
Beamforming methods are used extensively in a variety of different areas, where one of their main goals is to estimate the source signal amplitude s(t) from the array observations y(t) = s(t)a + i(t) + e(t), t = 1,2,..., where a is the steering vector, i(t) is the interference, and e(t) is a Gaussian noise vector [1, 2]. To estimate s(t), we may use a beamformer with weights w so that s(t) = w*...
متن کاملOptimal Mean Squared Error Imaging
The problem of forming images that are optimal with respect to a Mean Square Error (MSE) criterion, based on nite data, is considered. First, it is shown that the MSE criterion is consistent with the general goal of classifying images, in that decreasing the MSE guarantees a decrease in the probability of misclassifying an image. The problem of choosing sampling locations for image formation th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2017
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2017.2745450