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barcode generator for ssrs (a) xa(t) is real with Xu(f ) nonzero only for 9 kHz < ( f1 < 12 kHz. in Software
(a) xa(t) is real with Xu(f ) nonzero only for 9 kHz < ( f1 < 12 kHz. Decoding ANSI/AIM Code 128 In None Using Barcode Control SDK for Software Control to generate, create, read, scan barcode image in Software applications. USS Code 128 Generator In None Using Barcode maker for Software Control to generate, create USS Code 128 image in Software applications. (b) xa(t) is real with X u (f ) nonzero only for 18 kHz < 1 f 1 < 22 kHz.
Code128 Decoder In None Using Barcode scanner for Software Control to read, scan read, scan image in Software applications. Making Code 128A In C# Using Barcode creation for .NET framework Control to generate, create Code 128 Code Set C image in Visual Studio .NET applications. (c) xa(t) is complex with X,( f ) nonzero only for 30 kHz < f < 35 kHz.
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Creating 1D In .NET Using Barcode generation for ASP.NET Control to generate, create 1D image in ASP.NET applications. Making EAN128 In VB.NET Using Barcode generation for Visual Studio .NET Control to generate, create EAN128 image in VS .NET applications. For a (B + I)bit quantizer, the signaltoquantization noise ratio is SQNR = 6.02B With X , = 30, this becomes ,, SQNR = 6.02B x + 10.8 1  2010g m ,, + 10.81  20l0g3 = 6.02B + 10.81  9.54 = 6.02B + 1.27
If we want a signaltoquantization noise ratio of 90 dB, we require
An image is to be sampled with a signaltoquantization noise ratio of at least 80 dB. Unlike many other signals, the image samples are nonnegative. Assume that the sampling device is calibrated so that the sampled image intensities fall within the range from 0 to 1. How many bits are needed to achieve the desired signaltoquantization noise ratio For a bipolar signal with amplitudes that fall within the range [X,,,,, is
X,,,], the signaltoquantization noise ratio
SQNR = 6.02B + 10.81  201og& For a nonnegative signal that is confined to the interval [0, I], the signaltoquantization noise ratio is equivalent to the bipolar case if we set X,,, = 0.5. If we assume that the intensities of the image are uniformly distributed over the interval [0, I], u2 = I Therefore, SQNR = 6.02B
rn + 10.81  2010g  = 6.02B + 6.03 2
and for a signaltoquantization noise ratio of 80 dB, we require
or B
+ 1 = 14 bits.
Suppose that we have a set of unquantized samples, x(n), that are nonnegative for all n. A method for quantizing x ( n ) that is often used in speech processing is as follows. First, we form the sequence y(n) = log[x(n)l Then y(n) is quantized with a (B + 1)bit uniform quantizer, 9(n) = C [y(n)l = y(n) + e(n) W ) = exp(9(n)) The quantized signal samples are then obtained by exponentiating J(n), Show that if' e(n) is small, the signaltoquantization noise ratio is independent of the signal power. SAMPLING
we have, for R(n), R(n) = exp{log[x(n)l < If e(n) < 1, we may use the expansion to write &n) = x(n)l I + e(n)} = x(n) . exp(e(n)) exp{e(n)) x 1
+ e(n) + e(n)] = x(n) + f (n) where f (n) = x(n)e(n) is a (signaldependent) quantization noise. If we assume that the quantization noise e(n) is statistically independent of x(n), Elf2(n)) = ~ { x ~ ( n E{e2(n)) )}. and the signaltoquantization noise ratio is E{x2(n)l SQNR = 10 log  10 log E (e2(n)) = E { f '(n)) which is independent of the signal power. DiscreteTime Processing of Analog Signals
A continuoustime signal xa(t) is to be filtered to remove frequency components in the range 5 kHz 5 f i 10 kHz. The maximum frequency present in xa(t) is 20 kHz. The filtering is to be done by sampling x,(t), filtering the sampled signal, and reconstructing an analog signal using an ideal D/C converter. Find the minimum sampling frequency that may be used to avoid aliasing, and for this minimum sampling rate, find the frequency response of the ideal digital filter H ( e J m )that will remove the desired frequencies from xa (t). Because the highest frequency in x,(t) is 20 kHz, the minimum sampling frequency to avoid aliasing is f, = 40 kHz. The relationship between the continuous frequency variable R and the discrete frequency variable o is given by

