LGJul 5, 2025
Latent FxLMS: Accelerating Active Noise Control with Neural Adaptive FiltersKanad Sarkar, Austin Lu, Manan Mittal et al.
Filtered-X LMS (FxLMS) is commonly used for active noise control (ANC), wherein the soundfield is minimized at a desired location. Given prior knowledge of the spatial region of the noise or control sources, we could improve FxLMS by adapting along the low-dimensional manifold of possible adaptive filter weights. We train an auto-encoder on the filter coefficients of the steady-state adaptive filter for each primary source location sampled from a given spatial region and constrain the weights of the adaptive filter to be the output of the decoder for a given state of latent variables. Then, we perform updates in the latent space and use the decoder to generate the cancellation filter. We evaluate how various neural network constraints and normalization techniques impact the convergence speed and steady-state mean squared error. Under certain conditions, our Latent FxLMS model converges in fewer steps with comparable steady-state error to the standard FxLMS.
CRJul 11, 2012
IP over Voice-over-IP for censorship circumventionAmir Houmansadr, Thomas Riedl, Nikita Borisov et al.
Open communication over the Internet poses a serious threat to countries with repressive regimes, leading them to develop and deploy network-based censorship mechanisms within their networks. Existing censorship circumvention systems face different difficulties in providing unobservable communication with their clients; this limits their availability and poses threats to their users. To provide the required unobservability, several recent circumvention systems suggest modifying Internet routers running outside the censored region to intercept and redirect packets to censored destinations. However, these approaches require modifications to ISP networks, and hence requires cooperation from ISP operators and/or network equipment vendors, presenting a substantial deployment challenge. In this report we propose a deployable and unobservable censorship-resistant infrastructure, called FreeWave. FreeWave works by modulating a client's Internet connections into acoustic signals that are carried over VoIP connections. Such VoIP connections are targeted to a server, FreeWave server, that extracts the tunneled traffic of clients and proxies them to the uncensored Internet. The use of actual VoIP connections, as opposed to traffic morphing, allows FreeWave to relay its VoIP connections through oblivious VoIP nodes, hence keeping itself unblockable from censors that perform IP address blocking. Also, the use of end-to-end encryption prevents censors from identifying FreeWave's VoIP connections using packet content filtering technologies, like deep-packet inspection. We prototype the designed FreeWave system over the popular VoIP system of Skype. We show that FreeWave is able to reliably achieve communication bandwidths that are sufficient for web browsing, even when clients are far distanced from the FreeWave server.