Pregunta
upstudy study bank question image url

Consider a discrete-time WSS random process \( X(n) \) with autocorrelation function given by: \[ R_{x x}(k)=2 e^{-|k|} \] Then find the power spectral density of \( X(n) \).

Ask by Elliott Ryan. in Ethiopia
Jan 27,2025

Solución de tutoría real

Respuesta verificada por el tutor

Responder

The power spectral density \( S_X(e^{j\omega}) \) of the random process \( X(n) \) is: \[ S_X(e^{j\omega}) = \frac{2(1 - e^{-2})}{1 - 2 e^{-1} \cos \omega + e^{-2}} \]

Solución

To find the power spectral density \( S_X(e^{j\omega}) \) of the discrete-time wide-sense stationary (WSS) random process \( X(n) \) with autocorrelation function \( R_{XX}(k) = 2 e^{-|k|} \), we follow these steps: ### Step 1: Definition of Power Spectral Density The power spectral density of a discrete-time WSS process is given by the Fourier transform of its autocorrelation function: \[ S_X(e^{j\omega}) = \sum_{k=-\infty}^{\infty} R_{XX}(k) e^{-j\omega k} \] ### Step 2: Substitute the Autocorrelation Function Given \( R_{XX}(k) = 2 e^{-|k|} \), substitute this into the Fourier transform: \[ S_X(e^{j\omega}) = 2 \sum_{k=-\infty}^{\infty} e^{-|k|} e^{-j\omega k} \] ### Step 3: Evaluate the Summation The summation can be split into three parts: \( k = 0 \), \( k > 0 \), and \( k < 0 \): \[ \sum_{k=-\infty}^{\infty} e^{-|k|} e^{-j\omega k} = 1 + 2 \sum_{k=1}^{\infty} e^{-k} \cos(\omega k) \] This is a standard Fourier series, and its sum is known: \[ \sum_{k=-\infty}^{\infty} e^{-|k|} e^{-j\omega k} = \frac{1 - e^{-2}}{1 - 2 e^{-1} \cos \omega + e^{-2}} \] ### Step 4: Multiply by the Scaling Factor Finally, multiply by the scaling factor from the autocorrelation function: \[ S_X(e^{j\omega}) = 2 \cdot \frac{1 - e^{-2}}{1 - 2 e^{-1} \cos \omega + e^{-2}} \] ### Final Expression Thus, the power spectral density of \( X(n) \) is: \[ S_X(e^{j\omega}) = \frac{2(1 - e^{-2})}{1 - 2 e^{-1} \cos \omega + e^{-2}} \] **Answer:** After simplifying, it is equal to twice (1 – e⁻²) divided by [1 – 2 e⁻¹ cosω + e⁻²]. Thus, Sₓ(e^{jω}) = 2(1−e^{-2}) ⁄ [1−2e^{-1}cosω+e^{-2}]

Revisado y aprobado por el equipo de tutoría de UpStudy

error msg
Explicar
Simplifique esta solución

Mind Expander

To find the power spectral density \( S_{XX}(f) \) of the discrete-time wide-sense stationary (WSS) random process \( X(n) \), we can utilize the relationship between the autocorrelation function and the power spectral density through the Fourier transform. Given the autocorrelation function \( R_{XX}(k) = 2 e^{-|k|} \), we can compute the power spectral density by taking the discrete-time Fourier transform (DTFT) of \( R_{XX}(k) \): \[ S_{XX}(f) = \sum_{k=-\infty}^{\infty} R_{XX}(k) e^{-j 2 \pi f k} \] We can compute this sum by recognizing that \( R_{XX}(k) \) is an even function due to \( e^{-|k|} \), which allows us to break the sum into two parts: \[ S_{XX}(f) = \sum_{k=-\infty}^{-1} R_{XX}(k)e^{-j 2 \pi f k} + R_{XX}(0) + \sum_{k=1}^{\infty} R_{XX}(k)e^{-j 2 \pi f k} \] Substituting \( R_{XX}(k) \): \[ = \sum_{k=1}^{\infty} 2 e^{-k} e^{-j 2 \pi f k} + 2 + \sum_{k=1}^{\infty} 2 e^{-k} e^{j 2 \pi f k} \] This simplifies to: \[ = 2 + 2 \sum_{k=1}^{\infty} e^{-k(1+j 2 \pi f)} + 2 \sum_{k=1}^{\infty} e^{-k(1-j 2 \pi f)} \] Now, we recognize that \( \sum_{k=1}^{\infty} r^k = \frac{r}{1 - r} \) for \( |r| < 1 \). Therefore, \[ \sum_{k=1}^{\infty} e^{-k(1 \pm j 2 \pi f)} = \frac{e^{-(1 \pm j 2 \pi f)}}{1 - e^{-(1 \pm j 2 \pi f)}} = \frac{e^{-1}}{e^{-1 \pm j 2 \pi f} - 1} \] Substituting this back and simplifying yields: \[ S_{XX}(f) = 2 + 2 \left( \frac{e^{-1}}{1 - e^{-1 + j 2 \pi f}} + \frac{e^{-1}}{1 - e^{-1 - j 2 \pi f}} \right) \] After further manipulation and simplification, we arrive at the final expression for the power spectral density: \[ S_{XX}(f) = \frac{2 e^{-1}}{1 - e^{-1} e^{-j 2 \pi f}} + \frac{2 e^{-1}}{1 - e^{-1} e^{j 2 \pi f}} = \frac{2 e^{-1}}{1 - 2 e^{-1} \cos(2 \pi f) + e^{-2}} \] Thus, the power spectral density \( S_{XX}(f) \) of the random process \( X(n) \) is given by: \[ S_{XX}(f) = \frac{2 e^{-1}}{1 - 2 e^{-1} \cos(2 \pi f) + e^{-2}} \]

¡Prueba Premium ahora!
¡Prueba Premium y hazle a Thoth AI preguntas de matemáticas ilimitadas ahora!
Quizas mas tarde Hazte Premium
Estudiar puede ser una verdadera lucha
¿Por qué no estudiarlo en UpStudy?
Seleccione su plan a continuación
Prima

Puedes disfrutar

Empieza ahora
  • Explicaciones paso a paso
  • Tutores expertos en vivo 24/7
  • Número ilimitado de preguntas
  • Sin interrupciones
  • Acceso completo a Respuesta y Solución
  • Acceso completo al chat de PDF, al chat de UpStudy y al chat de navegación
Básico

Totalmente gratis pero limitado

  • Solución limitada
Bienvenido a ¡Estudia ahora!
Inicie sesión para continuar con el recorrido de Thoth AI Chat
Continuar con correo electrónico
O continuar con
Al hacer clic en "Iniciar sesión", acepta nuestros términos y condiciones. Términos de Uso & Política de privacidad