What defines a Pseudospectral Method?

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I'm trying to understand pseudospectral methods in the context of solving PDEs. However, I can't seem to find a solid definition for this.

Is it simply a general term for solving a problem in parts: partly in the time domain and partly in the spectral domain (via the Fourier transform)?

Any good references or tips welcomed! Thanks.

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Spectral methods look for approximations of solutions of an equation as a linear combination of a determined set of fucnctions, ussualy a a complete orthonormal system with respect to some weight. The firs step is to be able to approximate a function in that way . To fix things, fix an interval $[a,b]$ and a complete orthonormal system $\{\phi_k(x)\}_{k=1}^\infty$ with respect to a weighrt $w\colon[a,b]\to(0,\infty)$: $$ \int_a^b\phi_i(x)\,\phi_j(x)\,w(x)\,dx=\begin{cases}0 & \text{if }i\ne j,\\1 & \text{if }i=j.\end{cases} $$ For any $f\in L^2([a,b],w)$, that is, $\int_a^b|f|^2\,w\,dx<\infty$, we have $$ f=\sum_{k=1}^\infty\hat{f_k}\,\phi_k(x),\quad \hat{f_k}=\int_a^bf(x)\,\phi_k(x)\,w(x)\,dx, $$ with convergence in the $L^2$ sense. We approximate $f$ by the partial sum $$ f_N=\sum_{k=1}^N\hat{f_k}\,\phi_k(x). $$ This is an espectral approximations. In practice we may not know the function $f$ , but only its values at certain points $\{x_k\}_{k=1}^N$. Then we approximate $f$ by $$ \tilde{f_N}=\sum_{k=1}^N\tilde{f_k}\,\phi_k(x) $$ where the coefficients $\tilde{f_k}$ are chosen so that $f$ and $\tilde{f}$ coincide at the collocation points $\{x_k\}_{k=1}^N$. This is a pseudoespectral approximation.