A pseudo-noise (PN) sequence is generated using a feedback shift

A pseudo-noise (PN) sequence is generated using a feedback shift A pseudo-noise (PN) sequence is generated using a feedback shift register of length m = 4. The chip rate is 107 chips per second. Find the following parameters: (a) PN sequence length. (b) Chop duration of the PN sequence. (c) PN sequence period. Is this […]

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A randomly generated data stream consists of equiprobable binary

A randomly generated data stream consists of equiprobable binary A randomly generated data stream consists of equiprobable binary symbols 0 and 1. It is encoded into a polar nonreturn-to-zero waveform with each binary symbol being defined as follows: (a) Sketch the waveform so generated, assuming that the data stream is 00101110. (b) Derive an expression […]

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A random telegraph signal X (t), characterized by the autocorrel

A random telegraph signal X (t), characterized by the autocorrel A random telegraph signal X (t), characterized by the autocorrelation function RX (t) = exp (-2v |t |) Where v is a constant, is applied to the low-pass RC filter of Figure. Determine the power spectral density and autocorrelation function of the random process at […]

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A random process Y (t) consists of DC components of √3/2 v

A random process Y (t) consists of DC components of √3/2 v A random process Y (t) consists of DC components of v3/2 volts, a periodic component g (t), and a random component X (t). The autocorrelation function of Y (t) is shown in Figure. (a) What is the average power of the periodic components […]

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A one-step linear predictor operates on the sampled version

A one-step linear predictor operates on the sampled version A one-step linear predictor operates on the sampled version of a sinusoidal signal. The sampling rate is equal to l0 A?0 where A?0 is the frequency of the sinusoid. The predictor has a single coefficient denoted by w1. (a) Determine the optimum value of w1 required […]

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A practical limitation of an adaptive antenna array using the A practical limitation of an adaptive antenna array using the LMS algorithm is the dynamic ra

A practical limitation of an adaptive antenna array using the A practical limitation of an adaptive antenna array using the LMS algorithm is the dynamic ra A non-return-to-zero data stream (of amplitude levels ±1) is passed through a low-pa filter whose impulse response is defined by the Gaussian function where a is a design parameter […]

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A practical limitation of an adaptive antenna array using the

A practical limitation of an adaptive antenna array using the A practical limitation of an adaptive antenna array using the LMS algorithm is the dynamic range over which the array can operate. This limitation is due to the fact that the speed of response of the weights in the [MS algorithm is proportional to the […]

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